10223430
1
Jan van Rijn
3485
Supervised Classification
9666
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)(4)
8148862
copy
true
9559
fill_value
-1
9559
missing_values
NaN
9559
strategy
"constant"
9559
verbose
0
9559
n_jobs
null
9606
remainder
"passthrough"
9606
sparse_threshold
0.3
9606
transformer_weights
null
9606
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 238, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259, 260, 261, 262, 263, 264, 265, 266, 267, 268, 269, 270, 271, 272, 273, 274, 275, 276, 277, 278, 279, 280, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 292, 293]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [294, 295, 296, 297, 298]}}]
9606
memory
null
9607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
9607
axis
0
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copy
true
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missing_values
"NaN"
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strategy
"median"
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verbose
0
9608
copy
true
9609
with_mean
true
9609
with_std
true
9609
memory
null
9610
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
9610
categorical_features
null
9611
categories
null
9611
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
9611
handle_unknown
"ignore"
9611
n_values
null
9611
sparse
true
9611
threshold
0.0
9612
memory
null
9666
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
9666
criterion
"mse"
9667
init
null
9667
learning_rate
0.0049120097142137005
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loss
"deviance"
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max_depth
31
9667
max_features
0.6029597926778885
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max_leaf_nodes
null
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min_impurity_decrease
0.08027722789963387
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min_impurity_split
null
9667
min_samples_leaf
16
9667
min_samples_split
13
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min_weight_fraction_leaf
0.1324858559300236
9667
n_estimators
144
9667
n_iter_no_change
430
9667
presort
"auto"
9667
random_state
39911
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subsample
0.8838332154171349
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tol
0.0002844746152672428
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validation_fraction
0.8008343127385028
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verbose
0
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warm_start
false
9667
openml-python
Sklearn_0.20.3.
312
scene
https://www.openml.org/data/download/1390080/phpuZu33P
-1
21367776
description
https://api.openml.org/data/download/21367776/description.xml
-1
21367777
predictions
https://api.openml.org/data/download/21367777/predictions.arff
area_under_roc_curve
0.500107437744817 [0.500107,0.500107]
average_cost
0
kappa
0
kb_relative_information_score
93.69086298071007
mean_absolute_error
0.27892543854010743
mean_prior_absolute_error
0.29416743712946186
number_of_instances
2407 [1976,431]
predictive_accuracy
0.8209389281262983
prior_entropy
0.6786037019780878
recall
0.8209389281262983 [1,0]
relative_absolute_error
0.9481859761974725
root_mean_prior_squared_error
0.3834035412052162
root_mean_squared_error
0.38412173944366546
root_relative_squared_error
1.0018732175404317
total_cost
0
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
area_under_roc_curve
0.5 [0.5,0.5]
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
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kappa
0
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.458515118461609
kb_relative_information_score
9.336469762094362
kb_relative_information_score
9.201100835948266
kb_relative_information_score
9.201100835948266
kb_relative_information_score
9.201100835948266
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.2783886699092707
mean_absolute_error
0.28124817094269944
mean_absolute_error
0.2792259787222806
mean_absolute_error
0.2792259787222806
mean_absolute_error
0.2792259787222806
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.293758364638829
mean_prior_absolute_error
0.29641954703058604
mean_prior_absolute_error
0.2942351598173521
mean_prior_absolute_error
0.2942351598173521
mean_prior_absolute_error
0.2942351598173521
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [198,43]
number_of_instances
241 [197,44]
number_of_instances
240 [197,43]
number_of_instances
240 [197,43]
number_of_instances
240 [197,43]
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8215767634854773
predictive_accuracy
0.8174273858921162
predictive_accuracy
0.8208333333333333
predictive_accuracy
0.8208333333333333
predictive_accuracy
0.8208333333333333
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
prior_entropy
0.6786037019780878
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8215767634854771 [1,0]
recall
0.8174273858921162 [1,0]
recall
0.8208333333333333 [1,0]
recall
0.8208333333333333 [1,0]
recall
0.8208333333333333 [1,0]
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9476791248192878
relative_absolute_error
0.9488178959860527
relative_absolute_error
0.9489891653180113
relative_absolute_error
0.9489891653180113
relative_absolute_error
0.9489891653180113
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3828696944367244
root_mean_prior_squared_error
0.3863293741224291
root_mean_prior_squared_error
0.38349184880071946
root_mean_prior_squared_error
0.38349184880071946
root_mean_prior_squared_error
0.38349184880071946
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.38355842884966956
root_mean_squared_error
0.3872680846326686
root_mean_squared_error
0.3841947535744088
root_mean_squared_error
0.3841947535744088
root_mean_squared_error
0.3841947535744088
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0017988741938908
root_relative_squared_error
1.0024298191468661
root_relative_squared_error
1.0018329066859897
root_relative_squared_error
1.0018329066859897
root_relative_squared_error
1.0018329066859897
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
461.83948000179953
usercpu_time_millis
399.5720410021022
usercpu_time_millis
395.30116700188955
usercpu_time_millis
402.8139740039478
usercpu_time_millis
391.66533700336004
usercpu_time_millis
394.0391290016123
usercpu_time_millis
394.0825399986352
usercpu_time_millis
394.95252999768127
usercpu_time_millis
397.293965001154
usercpu_time_millis
391.58950400087633
usercpu_time_millis_testing
4.080198999872664
usercpu_time_millis_testing
3.56173900217982
usercpu_time_millis_testing
3.5543000012694392
usercpu_time_millis_testing
3.576843002520036
usercpu_time_millis_testing
3.5194890006096102
usercpu_time_millis_testing
3.548623000824591
usercpu_time_millis_testing
3.5136779988533817
usercpu_time_millis_testing
3.431802997511113
usercpu_time_millis_testing
3.47724900348112
usercpu_time_millis_testing
3.4552739998616744
usercpu_time_millis_training
457.75928100192687
usercpu_time_millis_training
396.0103019999224
usercpu_time_millis_training
391.7468670006201
usercpu_time_millis_training
399.23713100142777
usercpu_time_millis_training
388.1458480027504
usercpu_time_millis_training
390.4905060007877
usercpu_time_millis_training
390.5688619997818
usercpu_time_millis_training
391.52072700017015
usercpu_time_millis_training
393.8167159976729
usercpu_time_millis_training
388.13423000101466