9910380
6892
Scikit-learn Bot
14
Supervised Classification
8834
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)
7839773
memory
null
8834
n_jobs
null
8835
remainder
"passthrough"
8835
sparse_threshold
0.3
8835
transformer_weights
null
8835
memory
null
8836
axis
0
8837
copy
true
8837
missing_values
"NaN"
8837
strategy
"mean"
8837
verbose
0
8837
copy
true
8838
with_mean
true
8838
with_std
true
8838
memory
null
8839
copy
true
8840
fill_value
-1
8840
missing_values
NaN
8840
strategy
"constant"
8840
verbose
0
8840
categorical_features
null
8841
categories
null
8841
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
8841
handle_unknown
"ignore"
8841
n_values
null
8841
sparse
true
8841
threshold
0.0
8842
criterion
"friedman_mse"
8843
init
null
8843
learning_rate
0.020282769978940487
8843
loss
"deviance"
8843
max_depth
7
8843
max_features
0.7836036941416182
8843
max_leaf_nodes
null
8843
min_impurity_decrease
0.5697604065266533
8843
min_impurity_split
null
8843
min_samples_leaf
14
8843
min_samples_split
6
8843
min_weight_fraction_leaf
0.05756936800261436
8843
n_estimators
310
8843
n_iter_no_change
332
8843
presort
"auto"
8843
random_state
32111
8843
subsample
0.39377183130047166
8843
tol
2.0241430669508063e-05
8843
validation_fraction
0.44322787711359146
8843
verbose
0
8843
warm_start
false
8843
openml-python
Sklearn_0.20.1.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
20741216
description
https://api.openml.org/data/download/20741216/description.xml
-1
20741217
predictions
https://api.openml.org/data/download/20741217/predictions.arff
area_under_roc_curve
0.970903611111111 [0.998783,0.9332,0.991494,0.977042,0.961078,0.988289,0.944953,0.983106,0.993492,0.9376]
average_cost
0
f_measure
0.778600144650901 [0.965517,0.717557,0.887179,0.819095,0.747423,0.859296,0.502538,0.839907,0.945,0.502488]
kappa
0.755
kb_relative_information_score
1434.0104677773822
mean_absolute_error
0.07662137978837867
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7789556919169282 [0.951456,0.73057,0.910526,0.823232,0.771277,0.863636,0.510309,0.78355,0.945,0.5]
predictive_accuracy
0.7795000000000001
prior_entropy
3.321928094887362
recall
0.7795 [0.98,0.705,0.865,0.815,0.725,0.855,0.495,0.905,0.945,0.505]
relative_absolute_error
0.42567433215764616
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.17790080044286802
root_relative_squared_error
0.5930026681428844
total_cost
0
area_under_roc_curve
0.9683888888888889 [0.993056,0.913056,0.990556,0.966389,0.967222,0.999167,0.923333,0.98,0.9975,0.953611]
area_under_roc_curve
0.9641111111111113 [0.999722,0.925278,0.991944,0.961667,0.941944,0.985556,0.956667,0.945556,0.985556,0.947222]
area_under_roc_curve
0.9704444444444446 [0.999722,0.928056,0.994444,0.9775,0.950278,0.984444,0.930833,0.981944,1,0.957222]
area_under_roc_curve
0.9713055555555558 [0.999722,0.906667,0.997778,0.9875,0.984167,0.976667,0.968056,0.983056,0.984167,0.925278]
area_under_roc_curve
0.9672777777777776 [1,0.910278,0.992222,0.964722,0.944444,0.993056,0.956667,0.981389,1,0.93]
area_under_roc_curve
0.9729166666666668 [0.999722,0.92,0.995556,0.9925,0.975833,0.986944,0.941944,0.992222,0.998889,0.925556]
area_under_roc_curve
0.976722222222222 [0.997778,0.959167,0.983611,0.980556,0.975,0.979444,0.966111,0.988333,0.998333,0.938889]
area_under_roc_curve
0.9771944444444445 [1,0.946944,0.987222,0.986111,0.959722,0.994167,0.9475,0.995278,0.998333,0.956667]
area_under_roc_curve
0.9782222222222222 [1,0.948056,0.999167,0.994167,0.975278,0.990278,0.946944,0.994722,1,0.933611]
area_under_roc_curve
0.9681111111111111 [1,0.9825,0.989444,0.966667,0.946111,0.998333,0.9175,0.988889,0.977222,0.914444]
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
average_cost
0
f_measure
0.75547222769071 [0.95,0.697674,0.85,0.842105,0.727273,0.974359,0.465116,0.789474,0.883721,0.375]
f_measure
0.7599149887339876 [0.97561,0.682927,0.833333,0.829268,0.631579,0.780488,0.578947,0.727273,0.974359,0.585366]
f_measure
0.7908402731468975 [0.974359,0.75,0.864865,0.731707,0.790698,0.842105,0.545455,0.878049,0.97561,0.555556]
f_measure
0.794782516014865 [0.97561,0.685714,0.947368,0.857143,0.755556,0.789474,0.555556,0.829268,0.974359,0.577778]
f_measure
0.7862801926784654 [1,0.631579,0.923077,0.780488,0.705882,0.863636,0.555556,0.844444,1,0.55814]
f_measure
0.7894746716697935 [0.97561,0.777778,0.9,0.871795,0.820513,0.857143,0.47619,0.888889,0.926829,0.4]
f_measure
0.7917896026505169 [0.9,0.75,0.894737,0.829268,0.787879,0.857143,0.564103,0.869565,0.952381,0.512821]
f_measure
0.7819702615173852 [0.930233,0.714286,0.871795,0.8,0.842105,0.864865,0.5,0.883721,0.888889,0.52381]
f_measure
0.781519973292158 [1,0.648649,0.97561,0.9,0.666667,0.85,0.4,0.863636,1,0.510638]
f_measure
0.7474192998711612 [0.97561,0.829268,0.809524,0.742857,0.736842,0.918919,0.390244,0.818182,0.871795,0.380952]
kappa
0.7333333333333334
kappa
0.7333333333333334
kappa
0.7666666666666667
kappa
0.7722222222222223
kappa
0.7666666666666667
kappa
0.7722222222222223
kappa
0.7722222222222223
kappa
0.7555555555555555
kappa
0.7611111111111112
kappa
0.7166666666666667
kb_relative_information_score
142.26867297919367
kb_relative_information_score
141.33823906825353
kb_relative_information_score
142.80002931006516
kb_relative_information_score
144.3393588123791
kb_relative_information_score
142.3229482236757
kb_relative_information_score
145.48093601628025
kb_relative_information_score
144.2938388602709
kb_relative_information_score
145.54943681911374
kb_relative_information_score
146.6471475258072
kb_relative_information_score
138.9698601623452
mean_absolute_error
0.07826509147358585
mean_absolute_error
0.07702105843291637
mean_absolute_error
0.07768041133140435
mean_absolute_error
0.07502375836267111
mean_absolute_error
0.07744015695315343
mean_absolute_error
0.07500170492996229
mean_absolute_error
0.07636430218340017
mean_absolute_error
0.07430260318945325
mean_absolute_error
0.07488927599164344
mean_absolute_error
0.08022543503559774
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.7601932367149757 [0.95,0.652174,0.85,0.888889,0.666667,1,0.434783,0.833333,0.826087,0.5]
precision
0.7643849206349206 [0.952381,0.666667,0.9375,0.809524,0.666667,0.761905,0.611111,0.666667,1,0.571429]
precision
0.7968005318069257 [1,0.75,0.941176,0.714286,0.73913,0.888889,0.5,0.857143,0.952381,0.625]
precision
0.8038419913419914 [0.952381,0.8,1,0.818182,0.68,0.833333,0.625,0.809524,1,0.52]
precision
0.7931488503868366 [1,0.666667,0.947368,0.761905,0.857143,0.791667,0.625,0.76,1,0.521739]
precision
0.7908378901799955 [0.952381,0.875,0.9,0.894737,0.842105,0.818182,0.454545,0.8,0.904762,0.466667]
precision
0.8005734908366486 [0.9,0.75,0.944444,0.809524,1,0.818182,0.578947,0.769231,0.909091,0.526316]
precision
0.7902272557313611 [0.869565,0.681818,0.894737,0.8,0.888889,0.941176,0.5,0.826087,1,0.5]
precision
0.7861041083099906 [1,0.705882,0.952381,0.9,0.75,0.85,0.466667,0.791667,1,0.444444]
precision
0.7568402065770488 [0.952381,0.809524,0.772727,0.866667,0.777778,1,0.380952,0.75,0.894737,0.363636]
predictive_accuracy
0.76
predictive_accuracy
0.76
predictive_accuracy
0.79
predictive_accuracy
0.795
predictive_accuracy
0.79
predictive_accuracy
0.795
predictive_accuracy
0.795
predictive_accuracy
0.78
predictive_accuracy
0.785
predictive_accuracy
0.745
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
prior_entropy
3.321928094887362
recall
0.76 [0.95,0.75,0.85,0.8,0.8,0.95,0.5,0.75,0.95,0.3]
recall
0.76 [1,0.7,0.75,0.85,0.6,0.8,0.55,0.8,0.95,0.6]
recall
0.79 [0.95,0.75,0.8,0.75,0.85,0.8,0.6,0.9,1,0.5]
recall
0.795 [1,0.6,0.9,0.9,0.85,0.75,0.5,0.85,0.95,0.65]
recall
0.79 [1,0.6,0.9,0.8,0.6,0.95,0.5,0.95,1,0.6]
recall
0.795 [1,0.7,0.9,0.85,0.8,0.9,0.5,1,0.95,0.35]
recall
0.795 [0.9,0.75,0.85,0.85,0.65,0.9,0.55,1,1,0.5]
recall
0.78 [1,0.75,0.85,0.8,0.8,0.8,0.5,0.95,0.8,0.55]
recall
0.785 [1,0.6,1,0.9,0.6,0.85,0.35,0.95,1,0.6]
recall
0.745 [1,0.85,0.85,0.65,0.7,0.85,0.4,0.9,0.85,0.4]
relative_absolute_error
0.4348060637421441
relative_absolute_error
0.4278947690717581
relative_absolute_error
0.43155784073002473
relative_absolute_error
0.4167986575703955
relative_absolute_error
0.43022309418418614
relative_absolute_error
0.41667613849979096
relative_absolute_error
0.4242461232411125
relative_absolute_error
0.41279223994140746
relative_absolute_error
0.41605153328690847
relative_absolute_error
0.4456968613088768
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.18171372607140748
root_mean_squared_error
0.18613782802992102
root_mean_squared_error
0.17730975388515344
root_mean_squared_error
0.1753570182763392
root_mean_squared_error
0.18097843543302022
root_mean_squared_error
0.17362756566544407
root_mean_squared_error
0.1755575745862961
root_mean_squared_error
0.17288075093405392
root_mean_squared_error
0.1707920021214874
root_mean_squared_error
0.1839921094954762
root_relative_squared_error
0.6057124202380253
root_relative_squared_error
0.6204594267664038
root_relative_squared_error
0.5910325129505118
root_relative_squared_error
0.5845233942544644
root_relative_squared_error
0.6032614514434012
root_relative_squared_error
0.5787585522181473
root_relative_squared_error
0.585191915287654
root_relative_squared_error
0.5762691697801801
root_relative_squared_error
0.5693066737382917
root_relative_squared_error
0.6133070316515876
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
total_cost
0
usercpu_time_millis
6966.80530699814
usercpu_time_millis
6916.125051000563
usercpu_time_millis
6913.909523002076
usercpu_time_millis
6931.146793001972
usercpu_time_millis
6963.061682003172
usercpu_time_millis
6945.2913039967825
usercpu_time_millis
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usercpu_time_millis
6924.392445002013
usercpu_time_millis
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usercpu_time_millis
6935.729298998922
usercpu_time_millis_testing
9.49982999736676
usercpu_time_millis_testing
10.02491200051736
usercpu_time_millis_testing
9.373696000693599
usercpu_time_millis_testing
9.206144000927452
usercpu_time_millis_testing
9.449643002881203
usercpu_time_millis_testing
9.965763998479815
usercpu_time_millis_testing
9.819582999625709
usercpu_time_millis_testing
9.3917699996382
usercpu_time_millis_testing
9.48028300263104
usercpu_time_millis_testing
9.285678999731317
usercpu_time_millis_training
6957.305477000773
usercpu_time_millis_training
6906.100139000046
usercpu_time_millis_training
6904.535827001382
usercpu_time_millis_training
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usercpu_time_millis_training
6953.612039000291
usercpu_time_millis_training
6935.325539998303
usercpu_time_millis_training
6915.5081499993685
usercpu_time_millis_training
6915.000675002375
usercpu_time_millis_training
6928.565697999147
usercpu_time_millis_training
6926.443619999191