Algorithm Walk-Through¶
This notebook will walkthrough the preprocessing steps as well as the ML algorithm training procedure used for the multi-dimensional, multi-output data.
Experiment Overview¶
Code¶
Packages¶
import sys
sys.path.insert(0, "/media/disk/erc/papers/2019_ML_OCN/ml4ocean/src")
# Standard packages
import numpy as np
import pandas as pd
# Datasets
from data.make_dataset import DataLoader, load_standard_data, load_high_dim_data, load_labels
# Features
from features.build_features import times_2_cycles, geo_2_cartesian, get_geodataframe, CycleTransform, GeoCartTransform
from features.pca_features import transform_all, transform_individual
from features.analysis import get_stats
from sklearn.preprocessing import StandardScaler
from data.make_dataset import ValidationFloats
# ML Models
from sklearn.model_selection import train_test_split
from models.baseline import train_rf_model
import statsmodels.api as smi
# Visualization
from visualization.visualize import plot_mo_stats, plot_geolocations, get_depth_labels
from sklearn.inspection import permutation_importance
import matplotlib.pyplot as plt
plt.style.use('seaborn-poster')
%load_ext autoreload
%autoreload 2
--------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) <ipython-input-1-cfd0029a69eb> in <module> 7 8 # Datasets ----> 9 from data.make_dataset import DataLoader, load_standard_data, load_high_dim_data, load_labels 10 11 # Features /media/disk/erc/papers/2019_ML_OCN/ml4ocean/src/data/make_dataset.py in <module> 3 import numpy as np 4 from typing import Tuple, Optional, List ----> 5 from visualization.visualize import get_depth_labels 6 7 DATA_PATH = "/home/emmanuel/projects/2020_ml_ocn/data/RAW/CONTROL/" /media/disk/erc/papers/2019_ML_OCN/ml4ocean/src/visualization/visualize.py in <module> 1 from typing import Optional, List ----> 2 import geopandas as gpd 3 import pandas as pd 4 import numpy as np 5 import matplotlib.colors as colors ModuleNotFoundError: No module named 'geopandas'
1 Load Data¶
1.1 Core Data¶
In this step, we will load the standard data. This includes the following variables:
- SLA
- PAR
- RHO WN 412
- RHO WN 443
- RHO WN 490
- RHO WN 555
- RHO WN 670
- MLD
- Lat
- Lon
- DOY
X_core = load_standard_data('NA', training=True)
# Testing Data
X_core_te = load_standard_data('NA', training=False)
X_core_te = X_core_te.iloc[:, 2:]
X_core.shape, X_core_te.shape
--------------------------------------------------------------------------- NameError Traceback (most recent call last) <ipython-input-2-e3b9a45e5e2d> in <module> ----> 1 X_core = load_standard_data('NA', training=True) 2 3 # Testing Data 4 X_core_te = load_standard_data('NA', training=False) 5 NameError: name 'load_standard_data' is not defined
1.2 High Dimensional Data¶
In this section, we will extract the high dimensional datasets. They include:
- Temperature
- Density
- Salinity
- Spiciness
X_temp, X_dens, X_sal, X_spicy = load_high_dim_data('NA', training=True)
# add prefix (Training/Validation)
X_temp = X_temp.add_prefix('temp_')
X_dens = X_dens.add_prefix('dens_')
X_sal = X_sal.add_prefix('sal_')
X_spicy = X_spicy.add_prefix('spice_')
#
X_temp_te, X_dens_te, X_sal_te, X_spicy_te = load_high_dim_data('NA', training=False)
# Subset
X_temp_te = X_temp_te.iloc[:, 2:]
X_dens_te = X_dens_te.iloc[:, 2:]
X_sal_te= X_sal_te.iloc[:, 2:]
X_spicy_te = X_spicy_te.iloc[:, 2:]
# add prefix (Test)
X_temp_te = X_temp_te.add_prefix('temp_')
X_dens_te = X_dens_te.add_prefix('dens_')
X_sal_te = X_sal_te.add_prefix('sal_')
X_spicy_te = X_spicy_te.add_prefix('spice_')
1.3 - Multi-Output Data¶
We load the multioutput regression labels.
y = load_labels('NA', training=True)
yte = load_labels('NA', training=False)
yte = yte.iloc[:, 2:]
1.4 - Concatentate Data¶
# Training Data
Xtr = pd.concat([
X_core,
X_temp,
X_dens,
X_sal,
X_spicy
], axis=1)
# Testing Data
Xte = pd.concat([
X_core_te,
X_temp_te,
X_dens_te,
X_sal_te,
X_spicy_te
], axis=1)
Xtr.shape, Xte.shape
((2860, 1115), (162, 1115))
4 - Post-Split Transformations¶
- PCA Transform High Dimensional Variables
In this step, we do a PCA transformation on the concatenation for the high dimensional variables temp, sal, dens, and spicy. We will reduce the dimensionality to about 10 features.
- Normalize Core Variables
We will use a standard scaler to make the core variables with a mean of 0 and standard deviation of 1. The ML algorithms tend to perform better with this type of standardization.
- Coordinate Transformation
In this step, we will do a simple coordinate transformation of the lat,lon variables from geospatial to cartesian coordinates. This will increase the dimensionality of our dataset from 11 dimensions to 12 dimensions.
- Time Transformation
In this step, we will transform the doy coordinates to cycles of sines and cosines. This will increase the dimensionality of our data from from 12 to 13.
from sklearn.compose import ColumnTransformer
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.decomposition import PCA
# new columns columns
temp_columns = X_temp.columns.values
dens_columns = X_dens.columns.values
sal_columns = X_sal.columns.values
spicy_columns = X_spicy.columns.values
core_columns = ['sla', "PAR","RHO_WN_412","RHO_WN_443","RHO_WN_490","RHO_WN_555","RHO_WN_670","MLD"]
time_columns = ['doy']
loc_columns = ['lat', 'lon']
n_components = 5
times = ['doy']
new_columns = [
*["doy_cos", "doy_sin"],
*['x', 'y', 'z',],
*[f"temperature_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"density_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"salinity_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"spicy_pc{icomponent+1}" for icomponent in range(n_components)],
*core_columns,
]
seed = 123
# define transfomer
X_transformer = ColumnTransformer(
[ ("time", CycleTransform(times), time_columns),
("space", GeoCartTransform(), loc_columns),
('temp', PCA(n_components=n_components, random_state=seed), temp_columns),
('dens', PCA(n_components=n_components, random_state=seed), dens_columns),
('sal', PCA(n_components=n_components, random_state=seed), sal_columns),
('spice', PCA(n_components=n_components, random_state=seed), spicy_columns),
# ('standard', StandardScaler(with_mean=True, with_std=True), core_columns),
],
remainder='passthrough'
)
# fit transform to data
X_transformer.fit(Xtr)
# transform data
Xtrain = X_transformer.fit_transform(Xtr)
Xtest = X_transformer.transform(Xte)
# # X scaler
# X_scaler = StandardScaler(with_mean=True, with_std=True)
# Xtrain = X_scaler.fit_transform(Xtrain)
# Xtest = X_scaler.transform(Xtest)
Xtrain.shape, Xtest.shape
((2860, 33), (162, 33))
SAVE_PATH = "/media/disk/erc/papers/2019_ML_OCN/ml4ocean/reports/figures/"
SAVE_PATH = "/home/emmanuel/figures/ml4ocn/"
save_name = 'na'
# y_ticks = np.arange(0, len(feature_names))
plt.style.use(['seaborn-talk'])
fig, ax = plt.subplots(figsize=(7,5))
plt.plot(X_transformer.named_transformers_['temp'].explained_variance_ratio_[:25].cumsum(), linewidth=4, label='Temperature')
plt.plot(X_transformer.named_transformers_['dens'].explained_variance_ratio_[:25].cumsum(), linewidth=4, label='Density')
plt.plot(X_transformer.named_transformers_['sal'].explained_variance_ratio_[:25].cumsum(), linewidth=4, label='Salinity')
plt.plot(X_transformer.named_transformers_['spice'].explained_variance_ratio_[:25].cumsum(), linewidth=4, label='Spiciness')
# ax.set_title("Random Forest Feature Importances (MDI)")
ax.tick_params(axis="both", which="major", labelsize=20)
ax.tick_params(axis="both", which="minor", labelsize=20)
ax.grid(alpha=0.6, color='gray', zorder=0)
ax.set_ylim([0.8, 1.01])
plt.legend(fontsize=20, loc='lower right')
plt.tight_layout()
plt.show()
fig.savefig(SAVE_PATH + f"evar_{save_name}.png")
2.3 - Output Log Transformation¶
The distribution of the outputs are skewed because there is a lot more variability in the upper depths than the lower depths. Because the distribution of the outputs are fairly skewed, we propose to do a log transformation to make them normally distributed.
ytrain = np.log(y)
ytest = np.log(yte)
ytrain.shape, ytest.shape
((2860, 276), (162, 276))
3 - Train,Test Split¶
We split the data into 80% training and 20% training.
Note: because the dataset we are dealing with is only ~3,000 data points, we will do some bootstrap techniques in the full experiment to see how well we do with different subsamples of data.
Xtrain, Xvalid, ytrain, yvalid = train_test_split(
Xtrain, ytrain,
train_size=.8, random_state=1
)
X_transformer = StandardScaler(with_mean=True, with_std=True)
# fit transform to data
X_transformer.fit(Xtrain)
# transform data
Xtrain = X_transformer.fit_transform(Xtrain)
Xvalid = X_transformer.transform(Xvalid)
Xtest = X_transformer.transform(Xtest)
4.3 - Normalize Outputs¶
We will use the same standardization as shown above.
output_transformer = StandardScaler(with_mean=True, with_std=False)
ytrain = output_transformer.fit_transform(ytrain)
yvalid = output_transformer.fit_transform(yvalid)
ytest = output_transformer.transform(ytest)
5 - Train ML Model¶
from models.baseline import train_glm_model, train_gp_model, train_mlp_model, train_lr_model, train_mo_rf_model
5.1 - Linear Regression¶
model = train_lr_model(Xtrain, ytrain)
5.2 - Elastic Net (Cross-Validated)¶
model = train_gp_model(Xtrain, ytrain, verbose=2)
Training time: 325.695 secs.
5.3 - (2-Layer) MultiPerceptron Model¶
model = train_mlp_model(Xtrain, ytrain, verbose=1, valid=0.1)
Iteration 1, loss = 0.08259199 Iteration 2, loss = 0.06196244 Iteration 3, loss = 0.05127663 Iteration 4, loss = 0.04515546 Iteration 5, loss = 0.04057150 Iteration 6, loss = 0.03712973 Iteration 7, loss = 0.03477499 Iteration 8, loss = 0.03170803 Iteration 9, loss = 0.02916630 Iteration 10, loss = 0.02799048 Iteration 11, loss = 0.02599108 Iteration 12, loss = 0.02483116 Iteration 13, loss = 0.02389239 Iteration 14, loss = 0.02364000 Iteration 15, loss = 0.02151295 Iteration 16, loss = 0.02091288 Iteration 17, loss = 0.01989072 Iteration 18, loss = 0.01977638 Iteration 19, loss = 0.01826704 Iteration 20, loss = 0.01761360 Iteration 21, loss = 0.01709655 Iteration 22, loss = 0.01649704 Iteration 23, loss = 0.01630976 Iteration 24, loss = 0.01580504 Iteration 25, loss = 0.01569890 Iteration 26, loss = 0.01493390 Iteration 27, loss = 0.01418659 Iteration 28, loss = 0.01392162 Iteration 29, loss = 0.01358546 Iteration 30, loss = 0.01308379 Iteration 31, loss = 0.01287242 Iteration 32, loss = 0.01263431 Iteration 33, loss = 0.01235550 Iteration 34, loss = 0.01203142 Iteration 35, loss = 0.01185004 Iteration 36, loss = 0.01189953 Iteration 37, loss = 0.01165564 Iteration 38, loss = 0.01122221 Iteration 39, loss = 0.01117182 Iteration 40, loss = 0.01107617 Iteration 41, loss = 0.01078522 Iteration 42, loss = 0.01064290 Iteration 43, loss = 0.01065532 Iteration 44, loss = 0.01040591 Iteration 45, loss = 0.00990065 Iteration 46, loss = 0.00971778 Iteration 47, loss = 0.00987233 Iteration 48, loss = 0.00959703 Iteration 49, loss = 0.00939103 Iteration 50, loss = 0.00913538 Iteration 51, loss = 0.00902507 Iteration 52, loss = 0.00905964 Iteration 53, loss = 0.00920260 Iteration 54, loss = 0.00891849 Iteration 55, loss = 0.00862283 Iteration 56, loss = 0.00858086 Iteration 57, loss = 0.00839181 Iteration 58, loss = 0.00833643 Iteration 59, loss = 0.00848349 Iteration 60, loss = 0.00837573 Iteration 61, loss = 0.00813067 Iteration 62, loss = 0.00819205 Iteration 63, loss = 0.00792315 Iteration 64, loss = 0.00805537 Iteration 65, loss = 0.00771208 Iteration 66, loss = 0.00759574 Iteration 67, loss = 0.00748063 Iteration 68, loss = 0.00753782 Iteration 69, loss = 0.00731909 Iteration 70, loss = 0.00744589 Iteration 71, loss = 0.00730989 Iteration 72, loss = 0.00718921 Iteration 73, loss = 0.00696132 Iteration 74, loss = 0.00691535 Iteration 75, loss = 0.00698476 Iteration 76, loss = 0.00684462 Iteration 77, loss = 0.00665523 Iteration 78, loss = 0.00688687 Iteration 79, loss = 0.00698645 Iteration 80, loss = 0.00683245 Iteration 81, loss = 0.00678997 Iteration 82, loss = 0.00685581 Iteration 83, loss = 0.00670313 Iteration 84, loss = 0.00665865 Iteration 85, loss = 0.00641709 Iteration 86, loss = 0.00635330 Iteration 87, loss = 0.00642690 Iteration 88, loss = 0.00646101 Iteration 89, loss = 0.00642675 Iteration 90, loss = 0.00625143 Iteration 91, loss = 0.00618582 Iteration 92, loss = 0.00620553 Iteration 93, loss = 0.00625980 Iteration 94, loss = 0.00615398 Iteration 95, loss = 0.00647017 Iteration 96, loss = 0.00619490 Iteration 97, loss = 0.00596170 Iteration 98, loss = 0.00603269 Iteration 99, loss = 0.00592819 Iteration 100, loss = 0.00603444 Iteration 101, loss = 0.00615011 Iteration 102, loss = 0.00579275 Iteration 103, loss = 0.00568127 Iteration 104, loss = 0.00563711 Iteration 105, loss = 0.00554255 Iteration 106, loss = 0.00555402 Iteration 107, loss = 0.00554548 Iteration 108, loss = 0.00555376 Iteration 109, loss = 0.00546742 Iteration 110, loss = 0.00550522 Iteration 111, loss = 0.00545433 Iteration 112, loss = 0.00541275 Iteration 113, loss = 0.00538645 Iteration 114, loss = 0.00549167 Iteration 115, loss = 0.00552972 Iteration 116, loss = 0.00565934 Iteration 117, loss = 0.00554134 Iteration 118, loss = 0.00535729 Iteration 119, loss = 0.00537669 Iteration 120, loss = 0.00539923 Iteration 121, loss = 0.00544223 Iteration 122, loss = 0.00546966 Iteration 123, loss = 0.00558613 Iteration 124, loss = 0.00560681 Iteration 125, loss = 0.00529592 Iteration 126, loss = 0.00511268 Iteration 127, loss = 0.00514321 Iteration 128, loss = 0.00503528 Iteration 129, loss = 0.00501040 Iteration 130, loss = 0.00506291 Iteration 131, loss = 0.00506620 Iteration 132, loss = 0.00512712 Iteration 133, loss = 0.00513548 Iteration 134, loss = 0.00524527 Iteration 135, loss = 0.00515316 Iteration 136, loss = 0.00502089 Iteration 137, loss = 0.00497205 Iteration 138, loss = 0.00487709 Iteration 139, loss = 0.00487068 Iteration 140, loss = 0.00482505 Iteration 141, loss = 0.00478469 Iteration 142, loss = 0.00475009 Iteration 143, loss = 0.00481105 Iteration 144, loss = 0.00492210 Iteration 145, loss = 0.00491120 Iteration 146, loss = 0.00485862 Iteration 147, loss = 0.00491941 Iteration 148, loss = 0.00481827 Iteration 149, loss = 0.00476859 Iteration 150, loss = 0.00470496 Iteration 151, loss = 0.00464158 Iteration 152, loss = 0.00470730 Iteration 153, loss = 0.00480185 Iteration 154, loss = 0.00473243 Iteration 155, loss = 0.00482609 Iteration 156, loss = 0.00481751 Iteration 157, loss = 0.00471297 Iteration 158, loss = 0.00468560 Iteration 159, loss = 0.00477009 Iteration 160, loss = 0.00488836 Iteration 161, loss = 0.00482640 Iteration 162, loss = 0.00479873 Training loss did not improve more than tol=0.000010 for 10 consecutive epochs. Stopping. Training time: 24.616 secs.
5.4 - Random Forest Model¶
rf_model = train_rf_model(Xtrain, ytrain, verbose=2, n_jobs=1, mo_jobs=8)
[Parallel(n_jobs=1)]: Using backend SequentialBackend with 1 concurrent workers.
building tree 1 of 100
5.5 - Gaussian Process¶
model = train_gp_model(Xtrain, ytrain, verbose=1)
Training time: 528.233 secs.
6 - Test ML Model¶
6.1 - Training Data Results¶
This is often not reported but it is very good to check how well a model does on the initial training data because we have no entered a validation set. If we find that the training stats are too high and the testing stats are very low then we know that we're either overfitting and/or our model is not generalizing very well.
First we will look at the statistics on average to see what we get.
ypred = model.predict(Xtrain)
min_lim = np.min(np.concatenate((ypred, ytrain)))
max_lim = np.max(np.concatenate((ypred, ytrain)))
plt.scatter(ypred, ytrain)
plt.plot(np.linspace(min_lim, max_lim), np.linspace(min_lim, max_lim), color='black', zorder=3)
plt.xlim([min_lim, max_lim])
plt.ylim([min_lim, max_lim])
(-3.2836916337021815, 4.282232349201212)
stat_mod = smi.OLS(ypred.ravel(), ytrain.ravel())
res = stat_mod.fit()
print(res.summary())
OLS Regression Results
=======================================================================================
Dep. Variable: y R-squared (uncentered): 0.957
Model: OLS Adj. R-squared (uncentered): 0.957
Method: Least Squares F-statistic: 1.416e+07
Date: Mon, 27 Jan 2020 Prob (F-statistic): 0.00
Time: 12:19:53 Log-Likelihood: 6.7167e+05
No. Observations: 631488 AIC: -1.343e+06
Df Residuals: 631487 BIC: -1.343e+06
Df Model: 1
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
x1 0.9518 0.000 3762.815 0.000 0.951 0.952
==============================================================================
Omnibus: 189835.406 Durbin-Watson: 0.313
Prob(Omnibus): 0.000 Jarque-Bera (JB): 9389337.239
Skew: -0.681 Prob(JB): 0.00
Kurtosis: 21.841 Cond. No. 1.00
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
# each level
each_level = False
stats = get_stats(ypred, ytrain, each_level=each_level)
stats
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.06107 | 0.007378 | 0.007378 | 0.951758 |
Then we can look at the statistics for each level.
each_level = True
stats_df = get_stats(ypred, ytrain, each_level=each_level)
stats_df.head()
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.095378 | 0.017321 | 0.131608 | 0.971141 |
| 1 | 0.088260 | 0.014260 | 0.119415 | 0.976678 |
| 2 | 0.084835 | 0.012756 | 0.112944 | 0.979512 |
| 3 | 0.085067 | 0.012643 | 0.112440 | 0.979916 |
| 4 | 0.082786 | 0.011962 | 0.109371 | 0.980980 |
statistic = 'r2'
plt.style.use('seaborn-talk')
plot_mo_stats(stats_df, stat='r2', save_name='train_mlp')
plot_mo_stats(stats_df, stat='rmse', save_name='train_mlp')
6.2 - Testing Data Results¶
ypred = model.predict(Xtest)
min_lim = np.min(np.concatenate((ypred, ytest)))
max_lim = np.max(np.concatenate((ypred, ytest)))
plt.scatter(ypred, ytest)
plt.plot(np.linspace(min_lim, max_lim), np.linspace(min_lim, max_lim), color='black', zorder=3)
plt.xlim([min_lim, max_lim])
plt.ylim([min_lim, max_lim])
(-1.551942069352794, 2.87846572477131)
stat_mod = smi.OLS(ypred.ravel(), ytest.ravel())
res = stat_mod.fit()
print(res.summary())
OLS Regression Results
=======================================================================================
Dep. Variable: y R-squared (uncentered): 0.331
Model: OLS Adj. R-squared (uncentered): 0.331
Method: Least Squares F-statistic: 2.210e+04
Date: Mon, 27 Jan 2020 Prob (F-statistic): 0.00
Time: 12:20:01 Log-Likelihood: -4766.7
No. Observations: 44712 AIC: 9535.
Df Residuals: 44711 BIC: 9544.
Df Model: 1
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
x1 0.5448 0.004 148.665 0.000 0.538 0.552
==============================================================================
Omnibus: 2050.547 Durbin-Watson: 0.034
Prob(Omnibus): 0.000 Jarque-Bera (JB): 5794.388
Skew: 0.209 Prob(JB): 0.00
Kurtosis: 4.713 Cond. No. 1.00
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
each_level = True
stats_df = get_stats(ypred, ytest, each_level=each_level)
stats_df.head()
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.422045 | 0.281784 | 0.530833 | 0.490588 |
| 1 | 0.439044 | 0.299561 | 0.547322 | 0.487759 |
| 2 | 0.443207 | 0.312055 | 0.558618 | 0.490522 |
| 3 | 0.458520 | 0.327489 | 0.572267 | 0.487148 |
| 4 | 0.453541 | 0.327009 | 0.571847 | 0.496453 |
statistic = 'r2'
plt.style.use('seaborn-talk')
plot_mo_stats(stats_df, stat='r2', save_name='test_mlp')
plot_mo_stats(stats_df, stat='rmse', save_name='test_mlp')
6.3 - Validation Profile¶
ypred = model.predict(Xtest)
# initialize class
valid_getter = ValidationFloats('na')
# get validation floats
valid_getter.get_validation_floats('na')
[6901486, 3902123]
# get timeseries
y_validation = valid_getter.get_validation_res(ypred, ytest, 0)
y_validation.head()
(162, 2) (162, 276)
| n_cycle | Depth | Predictions | Test | |
|---|---|---|---|---|
| 0 | 3.0 | 0 | 1.005610 | 0.887168 |
| 1 | 12.0 | 0 | 0.818398 | 0.703823 |
| 2 | 24.0 | 0 | 1.029707 | 0.919995 |
| 3 | 25.0 | 0 | 1.062241 | 1.697790 |
| 4 | 26.0 | 0 | 1.066075 | 1.673884 |
model_name = 'mlp'
ifloat = 6901486
SAVE_PATH = "/home/emmanuel/figures/ml4ocn/"
min_lim = y_validation[['Predictions', 'Test']].min().min()
max_lim = y_validation[['Predictions', 'Test']].max().max()
plt.style.use('seaborn-talk')
fig, ax = plt.subplots()
y_validation.plot.scatter(ax=ax, x='Predictions', y='Test', c='n_cycle')
ax.plot(np.linspace(min_lim, max_lim), np.linspace(min_lim, max_lim), color='black', zorder=3)
plt.xlim([min_lim, max_lim])
plt.ylim([min_lim, max_lim])
plt.tight_layout()
plt.legend([r'R$^2$: 0.344', "coeff: 0.6386"], fontsize=20)
plt.savefig(SAVE_PATH + f'valid_m{model_name}_f{ifloat}_t' + '.png')
plt.show()
SAVE_PATH = "/home/emmanuel/figures/ml4ocn/"
min_lim = y_validation[['Predictions', 'Test']].min().min()
max_lim = y_validation[['Predictions', 'Test']].max().max()
plt.style.use('seaborn-talk')
fig, ax = plt.subplots()
y_validation.plot.scatter(ax=ax, x='Predictions', y='Test', c='Depth')
ax.plot(np.linspace(min_lim, max_lim), np.linspace(min_lim, max_lim), color='black', zorder=3)
plt.xlim([min_lim, max_lim])
plt.ylim([min_lim, max_lim])
plt.tight_layout()
plt.legend([r'R$^2$: 0.344', "coeff: 0.6386"], fontsize=20)
plt.savefig(SAVE_PATH + f'valid_m{model_name}_f{ifloat}_d' + '.png')
plt.show()
stat_mod = smi.OLS(y_validation['Predictions'], y_validation['Test'].ravel())
res = stat_mod.fit()
print(res.summary())
OLS Regression Results
=======================================================================================
Dep. Variable: Predictions R-squared (uncentered): 0.314
Model: OLS Adj. R-squared (uncentered): 0.314
Method: Least Squares F-statistic: 1.689e+04
Date: Mon, 27 Jan 2020 Prob (F-statistic): 0.00
Time: 12:20:15 Log-Likelihood: -8176.4
No. Observations: 36984 AIC: 1.635e+04
Df Residuals: 36983 BIC: 1.636e+04
Df Model: 1
Covariance Type: nonrobust
==============================================================================
coef std err t P>|t| [0.025 0.975]
------------------------------------------------------------------------------
x1 0.6573 0.005 129.966 0.000 0.647 0.667
==============================================================================
Omnibus: 5008.458 Durbin-Watson: 0.619
Prob(Omnibus): 0.000 Jarque-Bera (JB): 26607.874
Skew: 0.547 Prob(JB): 0.00
Kurtosis: 7.009 Cond. No. 1.00
==============================================================================
Warnings:
[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
# each level
each_level = False
stats = get_stats(ypred, ytest, each_level=each_level)
stats
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.239304 | 0.102378 | 0.102378 | -1.27019 |
each_level = True
stats_df = get_stats(ypred, ytest, each_level=each_level)
stats_df.head()
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.406305 | 0.267202 | 0.516915 | 0.516951 |
| 1 | 0.426680 | 0.294181 | 0.542385 | 0.496959 |
| 2 | 0.431409 | 0.302646 | 0.550133 | 0.505883 |
| 3 | 0.447864 | 0.317618 | 0.563576 | 0.502607 |
| 4 | 0.448236 | 0.322170 | 0.567600 | 0.503906 |
statistic = 'r2'
plt.style.use('seaborn-talk')
plot_mo_stats(stats_df, stat='r2', save_name='valid_mlp')
plot_mo_stats(stats_df, stat='rmse', save_name='valid_mlp')
7 - Post Analysis¶
7.1 - Feature Importance¶
For some algorithms, we can calculate the feature importance based on the inputs dimensions. This is true for the random forest model.
rf_model.
{'bootstrap': True,
'ccp_alpha': 0.0,
'criterion': 'mse',
'max_depth': None,
'max_features': 'auto',
'max_leaf_nodes': None,
'max_samples': None,
'min_impurity_decrease': 0.0,
'min_impurity_split': None,
'min_samples_leaf': 1,
'min_samples_split': 2,
'min_weight_fraction_leaf': 0.0,
'n_estimators': 1500,
'n_jobs': -1,
'oob_score': False,
'random_state': 123,
'verbose': 0,
'warm_start': False}
tree_feature_importances = \
rf_model.feature_importances_
feature_names = np.asarray(new_columns) #np.concatenate((core_columns.values, np.array(pca_columns)))
assert feature_names.shape[0] == tree_feature_importances.shape[0], "Shapes don't match"
sorted_idx = tree_feature_importances.argsort()
SAVE_PATH = "/media/disk/erc/papers/2019_ML_OCN/ml4ocean/reports/figures/"
save_name = 'na'
y_ticks = np.arange(0, len(feature_names))
plt.style.use(['seaborn-talk'])
fig, ax = plt.subplots(figsize=(10,10))
ax.barh(y_ticks, tree_feature_importances[sorted_idx], zorder=3, height=0.8)
ax.set_yticklabels(feature_names[sorted_idx])
ax.set_yticks(y_ticks)
# ax.set_title("Random Forest Feature Importances (MDI)")
ax.tick_params(axis="both", which="major", labelsize=20)
ax.tick_params(axis="both", which="minor", labelsize=20)
ax.grid(alpha=0.6, color='gray', zorder=0)
plt.tight_layout()
plt.show()
# fig.savefig(SAVE_PATH + f"fi_{save_name}.png")
7.2 - Permutation Plot¶
perm_result_test = permutation_importance(
rf_model,
Xtest,
ytest,
n_repeats=10,
random_state=42,
n_jobs=1
)
[Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.7s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.7s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 0.5s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 0.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning)
sorted_idx = perm_result_test.importances_mean.argsort()
fig, ax = plt.subplots(figsize=(10,10))
plt.style.use(['seaborn-talk'])
ax.boxplot(
perm_result_test.importances[sorted_idx].T,
vert=False,
labels=feature_names[sorted_idx]
)
ax.set_title("Permutation Importances (Test set)")
fig.tight_layout()
plt.show()
perm_result_train = permutation_importance(
rf_model,
Xtrain,
ytrain,
n_repeats=10,
random_state=42,
n_jobs=1
)
[Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.9s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.5s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.2s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.6s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.9s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.6s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.3s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.7s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.9s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.1s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.9s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.1s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.3s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.0s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.9s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.2s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.0s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.0s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.6s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.0s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.2s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.2s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.4s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.1s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.5s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.4s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.8s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.3s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 2.0s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.4s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.1s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.7s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.6s [Parallel(n_jobs=16)]: Done 768 tasks | elapsed: 1.1s [Parallel(n_jobs=16)]: Done 1218 tasks | elapsed: 1.8s [Parallel(n_jobs=16)]: Done 1500 out of 1500 | elapsed: 2.1s finished /home/emmanuel/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py:434: FutureWarning: The default value of multioutput (not exposed in score method) will change from 'variance_weighted' to 'uniform_average' in 0.23 to keep consistent with 'metrics.r2_score'. To specify the default value manually and avoid the warning, please either call 'metrics.r2_score' directly or make a custom scorer with 'metrics.make_scorer' (the built-in scorer 'r2' uses multioutput='uniform_average'). "multioutput='uniform_average').", FutureWarning) [Parallel(n_jobs=16)]: Using backend ThreadingBackend with 16 concurrent workers. [Parallel(n_jobs=16)]: Done 18 tasks | elapsed: 0.0s [Parallel(n_jobs=16)]: Done 168 tasks | elapsed: 0.3s [Parallel(n_jobs=16)]: Done 418 tasks | elapsed: 0.7s
--------------------------------------------------------------------------- KeyboardInterrupt Traceback (most recent call last) <ipython-input-38-bd4b09c39570> in <module> 5 n_repeats=10, 6 random_state=42, ----> 7 n_jobs=1 8 ) ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/inspection/_permutation_importance.py in permutation_importance(estimator, X, y, scoring, n_repeats, n_jobs, random_state) 116 scores = Parallel(n_jobs=n_jobs)(delayed(_calculate_permutation_scores)( 117 estimator, X, y, col_idx, random_seed, n_repeats, scorer --> 118 ) for col_idx in range(X.shape[1])) 119 120 importances = baseline_score - np.array(scores) ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in __call__(self, iterable) 1005 self._iterating = self._original_iterator is not None 1006 -> 1007 while self.dispatch_one_batch(iterator): 1008 pass 1009 ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in dispatch_one_batch(self, iterator) 833 return False 834 else: --> 835 self._dispatch(tasks) 836 return True 837 ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in _dispatch(self, batch) 752 with self._lock: 753 job_idx = len(self._jobs) --> 754 job = self._backend.apply_async(batch, callback=cb) 755 # A job can complete so quickly than its callback is 756 # called before we get here, causing self._jobs to ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/_parallel_backends.py in apply_async(self, func, callback) 207 def apply_async(self, func, callback=None): 208 """Schedule a func to be run""" --> 209 result = ImmediateResult(func) 210 if callback: 211 callback(result) ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/_parallel_backends.py in __init__(self, batch) 588 # Don't delay the application, to avoid keeping the input 589 # arguments in memory --> 590 self.results = batch() 591 592 def get(self): ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in __call__(self) 254 with parallel_backend(self._backend, n_jobs=self._n_jobs): 255 return [func(*args, **kwargs) --> 256 for func, args, kwargs in self.items] 257 258 def __len__(self): ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in <listcomp>(.0) 254 with parallel_backend(self._backend, n_jobs=self._n_jobs): 255 return [func(*args, **kwargs) --> 256 for func, args, kwargs in self.items] 257 258 def __len__(self): ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/inspection/_permutation_importance.py in _calculate_permutation_scores(estimator, X, y, col_idx, random_state, n_repeats, scorer) 32 else: 33 X_permuted[:, col_idx] = X_permuted[shuffling_idx, col_idx] ---> 34 feature_score = scorer(estimator, X_permuted, y) 35 scores[n_round] = feature_score 36 ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/metrics/_scorer.py in _passthrough_scorer(estimator, *args, **kwargs) 369 def _passthrough_scorer(estimator, *args, **kwargs): 370 """Function that wraps estimator.score""" --> 371 return estimator.score(*args, **kwargs) 372 373 ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/base.py in score(self, X, y, sample_weight) 420 from .metrics import r2_score 421 from .metrics._regression import _check_reg_targets --> 422 y_pred = self.predict(X) 423 # XXX: Remove the check in 0.23 424 y_type, _, _, _ = _check_reg_targets(y, y_pred, None) ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/sklearn/ensemble/_forest.py in predict(self, X) 780 **_joblib_parallel_args(require="sharedmem"))( 781 delayed(_accumulate_prediction)(e.predict, X, [y_hat], lock) --> 782 for e in self.estimators_) 783 784 y_hat /= len(self.estimators_) ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in __call__(self, iterable) 1015 1016 with self._backend.retrieval_context(): -> 1017 self.retrieve() 1018 # Make sure that we get a last message telling us we are done 1019 elapsed_time = time.time() - self._start_time ~/.conda/envs/ml4ocn/lib/python3.6/site-packages/joblib/parallel.py in retrieve(self) 907 try: 908 if getattr(self._backend, 'supports_timeout', False): --> 909 self._output.extend(job.get(timeout=self.timeout)) 910 else: 911 self._output.extend(job.get()) ~/.conda/envs/ml4ocn/lib/python3.6/multiprocessing/pool.py in get(self, timeout) 636 637 def get(self, timeout=None): --> 638 self.wait(timeout) 639 if not self.ready(): 640 raise TimeoutError ~/.conda/envs/ml4ocn/lib/python3.6/multiprocessing/pool.py in wait(self, timeout) 633 634 def wait(self, timeout=None): --> 635 self._event.wait(timeout) 636 637 def get(self, timeout=None): ~/.conda/envs/ml4ocn/lib/python3.6/threading.py in wait(self, timeout) 549 signaled = self._flag 550 if not signaled: --> 551 signaled = self._cond.wait(timeout) 552 return signaled 553 ~/.conda/envs/ml4ocn/lib/python3.6/threading.py in wait(self, timeout) 293 try: # restore state no matter what (e.g., KeyboardInterrupt) 294 if timeout is None: --> 295 waiter.acquire() 296 gotit = True 297 else: KeyboardInterrupt:
sorted_idx = perm_result_train.importances_mean.argsort()
plt.style.use(['seaborn-talk'])
fig, ax = plt.subplots()
ax.boxplot(
perm_result_train.importances[sorted_idx].T,
vert=False,
labels=feature_names[sorted_idx]
)
ax.set_title("Permutation Importances (Train set)")
fig.tight_layout()
plt.show()
Subtropical Gyros¶
Load Data¶
X_core = load_standard_data('STG', training=True)
# Testing Data
X_core_te = load_standard_data('STG', training=False)
X_core_te = X_core_te.iloc[:, 2:]
X_core.shape, X_core_te.shape
((1353, 11), (133, 11))
X_temp, X_dens, X_sal, X_spicy = load_high_dim_data('STG', training=True)
# add prefix (Training/Validation)
X_temp = X_temp.add_prefix('temp_')
X_dens = X_dens.add_prefix('dens_')
X_sal = X_sal.add_prefix('sal_')
X_spicy = X_spicy.add_prefix('spice_')
#
X_temp_te, X_dens_te, X_sal_te, X_spicy_te = load_high_dim_data('STG', training=False)
# Subset
X_temp_te = X_temp_te.iloc[:, 2:]
X_dens_te = X_dens_te.iloc[:, 2:]
X_sal_te= X_sal_te.iloc[:, 2:]
X_spicy_te = X_spicy_te.iloc[:, 2:]
# add prefix (Test)
X_temp_te = X_temp_te.add_prefix('temp_')
X_dens_te = X_dens_te.add_prefix('dens_')
X_sal_te = X_sal_te.add_prefix('sal_')
X_spicy_te = X_spicy_te.add_prefix('spice_')
y = load_labels('STG', training=True)
yte = load_labels('STG', training=False)
yte = yte.iloc[:, 2:]
# Training Data
Xtr = pd.concat([
X_core,
X_temp,
X_dens,
X_sal,
X_spicy
], axis=1)
# Testing Data
Xte = pd.concat([
X_core_te,
X_temp_te,
X_dens_te,
X_sal_te,
X_spicy_te
], axis=1)
Tre Transformations¶
# new columns columns
temp_columns = X_temp.columns.values
dens_columns = X_dens.columns.values
sal_columns = X_sal.columns.values
spicy_columns = X_spicy.columns.values
core_columns = ['sla', "PAR","RHO_WN_412","RHO_WN_443","RHO_WN_490","RHO_WN_555","RHO_WN_670","MLD"]
time_columns = ['doy']
loc_columns = ['lat', 'lon']
n_components = 5
times = ['doy']
new_columns = [
*["doy_cos", "doy_sin"],
*['x', 'y', 'z',],
*[f"temperature_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"density_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"salinity_pc{icomponent+1}" for icomponent in range(n_components)],
*[f"spicy_pc{icomponent+1}" for icomponent in range(n_components)],
*core_columns,
]
seed = 123
# define transfomer
X_transformer = ColumnTransformer(
[ ("time", CycleTransform(times), time_columns),
("space", GeoCartTransform(), loc_columns),
('temp', PCA(n_components=n_components, random_state=seed), temp_columns),
('dens', PCA(n_components=n_components, random_state=seed), dens_columns),
('sal', PCA(n_components=n_components, random_state=seed), sal_columns),
('spice', PCA(n_components=n_components, random_state=seed), spicy_columns),
# ('core', StandardScaler(with_mean=True, with_std=True), core_columns)
],
remainder='passthrough'
)
# fit transform to data
X_transformer.fit(Xtr)
# transform data
Xtrain = X_transformer.fit_transform(Xtr)
Xtest = X_transformer.transform(Xte)
ytrain = np.log(y)
ytest = np.log(yte)
ytrain.shape, ytest.shape
((1353, 276), (133, 276))
Train-Test Split¶
Xtrain, Xvalid, ytrain, yvalid = train_test_split(
Xtrain, ytrain,
train_size=.8, random_state=1
)
Post Transformations¶
X_transformer = StandardScaler(with_mean=True, with_std=True)
# fit transform to data
X_transformer.fit(Xtrain)
# transform data
Xtrain = X_transformer.fit_transform(Xtrain)
Xvalid = X_transformer.transform(Xvalid)
Xtest = X_transformer.transform(Xtest)
output_transformer = StandardScaler(with_mean=True, with_std=False)
ytrain = output_transformer.fit_transform(ytrain)
yvalid = output_transformer.fit_transform(yvalid)
ytest = output_transformer.transform(ytest)
Train ML Model¶
model = train_mlp_model(Xtrain, ytrain, verbose=1, valid=0.1)
Iteration 1, loss = 0.04404014 Iteration 2, loss = 0.04233716 Iteration 3, loss = 0.03999879 Iteration 4, loss = 0.03553489 Iteration 5, loss = 0.02922904 Iteration 6, loss = 0.02270823 Iteration 7, loss = 0.01774804 Iteration 8, loss = 0.01455149 Iteration 9, loss = 0.01275994 Iteration 10, loss = 0.01139479 Iteration 11, loss = 0.01041543 Iteration 12, loss = 0.00956958 Iteration 13, loss = 0.00893924 Iteration 14, loss = 0.00837105 Iteration 15, loss = 0.00784597 Iteration 16, loss = 0.00745897 Iteration 17, loss = 0.00710062 Iteration 18, loss = 0.00689064 Iteration 19, loss = 0.00659195 Iteration 20, loss = 0.00644984 Iteration 21, loss = 0.00620834 Iteration 22, loss = 0.00599103 Iteration 23, loss = 0.00585093 Iteration 24, loss = 0.00571502 Iteration 25, loss = 0.00557472 Iteration 26, loss = 0.00544984 Iteration 27, loss = 0.00532607 Iteration 28, loss = 0.00522278 Iteration 29, loss = 0.00508456 Iteration 30, loss = 0.00503143 Iteration 31, loss = 0.00501642 Iteration 32, loss = 0.00492858 Iteration 33, loss = 0.00483732 Iteration 34, loss = 0.00476257 Iteration 35, loss = 0.00471380 Iteration 36, loss = 0.00463958 Iteration 37, loss = 0.00454218 Iteration 38, loss = 0.00448899 Iteration 39, loss = 0.00441734 Iteration 40, loss = 0.00432583 Iteration 41, loss = 0.00428757 Iteration 42, loss = 0.00424003 Iteration 43, loss = 0.00421163 Iteration 44, loss = 0.00419324 Iteration 45, loss = 0.00413517 Iteration 46, loss = 0.00409957 Iteration 47, loss = 0.00404558 Iteration 48, loss = 0.00408237 Iteration 49, loss = 0.00397557 Iteration 50, loss = 0.00390968 Iteration 51, loss = 0.00390060 Iteration 52, loss = 0.00386618 Iteration 53, loss = 0.00382930 Iteration 54, loss = 0.00378482 Iteration 55, loss = 0.00374815 Iteration 56, loss = 0.00369985 Iteration 57, loss = 0.00370369 Iteration 58, loss = 0.00370657 Iteration 59, loss = 0.00364967 Iteration 60, loss = 0.00361953 Iteration 61, loss = 0.00363740 Iteration 62, loss = 0.00363886 Iteration 63, loss = 0.00364014 Iteration 64, loss = 0.00357380 Iteration 65, loss = 0.00354915 Iteration 66, loss = 0.00354744 Iteration 67, loss = 0.00356916 Iteration 68, loss = 0.00348918 Iteration 69, loss = 0.00345298 Iteration 70, loss = 0.00341895 Iteration 71, loss = 0.00338562 Iteration 72, loss = 0.00337161 Iteration 73, loss = 0.00333775 Iteration 74, loss = 0.00330174 Iteration 75, loss = 0.00328011 Iteration 76, loss = 0.00328366 Iteration 77, loss = 0.00327779 Iteration 78, loss = 0.00324590 Iteration 79, loss = 0.00322532 Iteration 80, loss = 0.00321512 Iteration 81, loss = 0.00322540 Iteration 82, loss = 0.00323972 Iteration 83, loss = 0.00319478 Iteration 84, loss = 0.00318867 Iteration 85, loss = 0.00315817 Iteration 86, loss = 0.00316153 Iteration 87, loss = 0.00317412 Iteration 88, loss = 0.00314881 Iteration 89, loss = 0.00316765 Iteration 90, loss = 0.00323642 Iteration 91, loss = 0.00315456 Iteration 92, loss = 0.00311508 Iteration 93, loss = 0.00310767 Iteration 94, loss = 0.00310070 Iteration 95, loss = 0.00311034 Iteration 96, loss = 0.00306191 Iteration 97, loss = 0.00303219 Iteration 98, loss = 0.00301453 Iteration 99, loss = 0.00300814 Iteration 100, loss = 0.00301214 Iteration 101, loss = 0.00296582 Iteration 102, loss = 0.00295890 Iteration 103, loss = 0.00294944 Iteration 104, loss = 0.00295457 Iteration 105, loss = 0.00295732 Iteration 106, loss = 0.00295811 Iteration 107, loss = 0.00291975 Iteration 108, loss = 0.00291308 Iteration 109, loss = 0.00293052 Iteration 110, loss = 0.00290656 Iteration 111, loss = 0.00291328 Iteration 112, loss = 0.00289352 Iteration 113, loss = 0.00288698 Iteration 114, loss = 0.00285006 Iteration 115, loss = 0.00286369 Iteration 116, loss = 0.00286365 Iteration 117, loss = 0.00285693 Iteration 118, loss = 0.00284021 Iteration 119, loss = 0.00280960 Iteration 120, loss = 0.00282471 Iteration 121, loss = 0.00282692 Iteration 122, loss = 0.00281811 Iteration 123, loss = 0.00280976 Iteration 124, loss = 0.00281109 Iteration 125, loss = 0.00278118 Iteration 126, loss = 0.00277009 Iteration 127, loss = 0.00277372 Iteration 128, loss = 0.00276675 Iteration 129, loss = 0.00273699 Iteration 130, loss = 0.00274575 Iteration 131, loss = 0.00277771 Iteration 132, loss = 0.00277319 Iteration 133, loss = 0.00276945 Iteration 134, loss = 0.00271861 Iteration 135, loss = 0.00270733 Iteration 136, loss = 0.00269192 Iteration 137, loss = 0.00268628 Iteration 138, loss = 0.00267595 Iteration 139, loss = 0.00267008 Iteration 140, loss = 0.00267025 Iteration 141, loss = 0.00266669 Iteration 142, loss = 0.00264064 Iteration 143, loss = 0.00266217 Iteration 144, loss = 0.00264794 Iteration 145, loss = 0.00263791 Iteration 146, loss = 0.00262205 Iteration 147, loss = 0.00261012 Iteration 148, loss = 0.00261269 Iteration 149, loss = 0.00260257 Iteration 150, loss = 0.00261959 Iteration 151, loss = 0.00260983 Iteration 152, loss = 0.00260160 Iteration 153, loss = 0.00259984 Iteration 154, loss = 0.00258859 Iteration 155, loss = 0.00260201 Iteration 156, loss = 0.00259312 Iteration 157, loss = 0.00258840 Iteration 158, loss = 0.00258678 Iteration 159, loss = 0.00257915 Iteration 160, loss = 0.00257172 Iteration 161, loss = 0.00255456 Iteration 162, loss = 0.00255829 Iteration 163, loss = 0.00256354 Iteration 164, loss = 0.00257048 Iteration 165, loss = 0.00256765 Iteration 166, loss = 0.00256455 Iteration 167, loss = 0.00256505 Iteration 168, loss = 0.00255623 Iteration 169, loss = 0.00253190 Iteration 170, loss = 0.00251063 Iteration 171, loss = 0.00250799 Iteration 172, loss = 0.00249209 Iteration 173, loss = 0.00248792 Iteration 174, loss = 0.00246772 Iteration 175, loss = 0.00246227 Iteration 176, loss = 0.00247650 Iteration 177, loss = 0.00247792 Iteration 178, loss = 0.00246150 Iteration 179, loss = 0.00245814 Iteration 180, loss = 0.00246831 Iteration 181, loss = 0.00245703 Iteration 182, loss = 0.00245560 Iteration 183, loss = 0.00244056 Iteration 184, loss = 0.00244849 Iteration 185, loss = 0.00246202 Iteration 186, loss = 0.00246362 Iteration 187, loss = 0.00247775 Iteration 188, loss = 0.00250301 Iteration 189, loss = 0.00253404 Iteration 190, loss = 0.00249942 Iteration 191, loss = 0.00247626 Iteration 192, loss = 0.00243972 Iteration 193, loss = 0.00241549 Iteration 194, loss = 0.00240424 Iteration 195, loss = 0.00240119 Iteration 196, loss = 0.00240227 Iteration 197, loss = 0.00241523 Iteration 198, loss = 0.00242200 Iteration 199, loss = 0.00243402 Iteration 200, loss = 0.00244168 Iteration 201, loss = 0.00244610 Iteration 202, loss = 0.00244003 Iteration 203, loss = 0.00241704 Iteration 204, loss = 0.00238488 Iteration 205, loss = 0.00236594 Iteration 206, loss = 0.00238378 Iteration 207, loss = 0.00239985 Iteration 208, loss = 0.00237313 Iteration 209, loss = 0.00236799 Iteration 210, loss = 0.00235266 Iteration 211, loss = 0.00235649 Iteration 212, loss = 0.00236750 Iteration 213, loss = 0.00237051 Iteration 214, loss = 0.00238517 Iteration 215, loss = 0.00238750 Iteration 216, loss = 0.00237986 Iteration 217, loss = 0.00237983 Iteration 218, loss = 0.00236825 Iteration 219, loss = 0.00236512 Iteration 220, loss = 0.00238062 Iteration 221, loss = 0.00239693 Training loss did not improve more than tol=0.000010 for 10 consecutive epochs. Stopping. Training time: 7.193 secs.
Test ML Model¶
ypred = model.predict(Xtest)
# each level
each_level = False
stats = get_stats(ypred, ytest, each_level=each_level)
stats
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.076336 | 0.011636 | 0.011636 | 0.812559 |
each_level = True
stats_df = get_stats(ypred, ytest, each_level=each_level)
stats_df.head()
| mae | mse | rmse | r2 | |
|---|---|---|---|---|
| 0 | 0.088556 | 0.020310 | 0.142513 | 0.717452 |
| 1 | 0.081911 | 0.015445 | 0.124277 | 0.762677 |
| 2 | 0.076586 | 0.011129 | 0.105496 | 0.814074 |
| 3 | 0.081023 | 0.013181 | 0.114808 | 0.789395 |
| 4 | 0.073182 | 0.009919 | 0.099596 | 0.820807 |
statistic = 'r2'
plt.style.use('seaborn-talk')
plot_mo_stats(
stats_df,
stat='r2',
save_name='stg_test',
color='red'
)
plot_mo_stats(stats_df, stat='mae', save_name='stg_test', color='red')
plot_mo_stats(stats_df, stat='mse', save_name='stg_test', color='red')
plot_mo_stats(stats_df, stat='rmse', save_name='stg_test', color='red')
Post Analysis¶
tree_feature_importances = \
rf_model.feature_importances_
feature_names = np.asarray(new_columns) #np.concatenate((core_columns.values, np.array(pca_columns)))
assert feature_names.shape[0] == tree_feature_importances.shape[0], "Shapes don't match"
sorted_idx = tree_feature_importances.argsort()
SAVE_PATH = "/media/disk/erc/papers/2019_ML_OCN/ml4ocean/reports/figures/"
save_name = 'stg'
y_ticks = np.arange(0, len(feature_names))
plt.style.use(['seaborn-talk'])
fig, ax = plt.subplots(figsize=(10,10))
ax.barh(y_ticks, tree_feature_importances[sorted_idx], zorder=3, height=0.8, color='red')
ax.set_yticklabels(feature_names[sorted_idx])
ax.set_yticks(y_ticks)
# ax.set_title("Random Forest Feature Importances (MDI)")
ax.tick_params(axis="both", which="major", labelsize=20)
ax.tick_params(axis="both", which="minor", labelsize=20)
ax.grid(alpha=0.6, color='gray', zorder=0)
plt.tight_layout()
plt.show()
fig.savefig(SAVE_PATH + f"fi_{save_name}.png")
depths = 276
first = [*range(1, 250)]
d1 = first[::2]
second = [*range(251,1000)]
d2 = second[::5]
len(d1), len(d2)
(125, 150)
plt.plot(-np.concatenate((d1,d2)))
[<matplotlib.lines.Line2D at 0x7f8ad6785a90>]
