10223626
1
Jan van Rijn
14967
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)
8149058
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": [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]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1]}}]
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
9608
copy
true
9608
missing_values
"NaN"
9608
strategy
"most_frequent"
9608
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
"friedman_mse"
9667
init
null
9667
learning_rate
0.0006133435988241978
9667
loss
"deviance"
9667
max_depth
26
9667
max_features
0.2435297987807048
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.252688373075712
9667
min_impurity_split
null
9667
min_samples_leaf
18
9667
min_samples_split
2
9667
min_weight_fraction_leaf
0.28642932270223836
9667
n_estimators
145
9667
n_iter_no_change
587
9667
presort
"auto"
9667
random_state
7508
9667
subsample
0.9995337351086007
9667
tol
0.009474525992204347
9667
validation_fraction
0.24090959291301617
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
23380
cjs
https://www.openml.org/data/download/1910442/phpDAC5gS
-1
21368168
description
https://api.openml.org/data/download/21368168/description.xml
-1
21368169
predictions
https://api.openml.org/data/download/21368169/predictions.arff
area_under_roc_curve
0.6135251034579936 [0.602213,0.584103,0.613045,0.502605,0.687249,0.770581]
average_cost
0
kappa
0
kb_relative_information_score
102.67466358453105
mean_absolute_error
0.27604794267185995
mean_prior_absolute_error
0.27287997162595995
number_of_instances
2796 [576,341,680,511,414,274]
predictive_accuracy
0.24320457796852646
prior_entropy
2.5206634795042744
recall
0.24320457796852646 [0,0,1,0,0,0]
relative_absolute_error
1.0116093937822683
root_mean_prior_squared_error
0.3693707377543301
root_mean_squared_error
0.37055721732267605
root_relative_squared_error
1.0032121644923997
total_cost
0
area_under_roc_curve
0.6180021607529842 [0.637387,0.554818,0.62715,0.49011,0.651495,0.816256]
area_under_roc_curve
0.5975159530267093 [0.587838,0.667683,0.566801,0.397808,0.70798,0.808957]
area_under_roc_curve
0.6490552530481953 [0.70014,0.540112,0.628989,0.552145,0.721196,0.795139]
area_under_roc_curve
0.6268135011175171 [0.588032,0.59248,0.655938,0.541014,0.673844,0.765519]
area_under_roc_curve
0.5840608434336741 [0.565121,0.686932,0.531944,0.528973,0.581131,0.737008]
area_under_roc_curve
0.6153448304355815 [0.584304,0.681691,0.606652,0.444173,0.730942,0.7657]
area_under_roc_curve
0.6204627970793335 [0.554173,0.5509,0.673752,0.494238,0.794254,0.681878]
area_under_roc_curve
0.6296987115921817 [0.679192,0.554382,0.613535,0.540119,0.62834,0.832084]
area_under_roc_curve
0.6156621257149187 [0.586257,0.557983,0.655701,0.471448,0.721469,0.757349]
area_under_roc_curve
0.6301665791718388 [0.606488,0.564586,0.624477,0.585569,0.66747,0.803277]
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
10.439742381245656
kb_relative_information_score
10.510319432528416
kb_relative_information_score
10.481657676772441
kb_relative_information_score
10.338028525251703
kb_relative_information_score
9.758599986333161
kb_relative_information_score
10.293627655383595
kb_relative_information_score
10.275148950478291
kb_relative_information_score
10.100222327860651
kb_relative_information_score
10.203801320775757
kb_relative_information_score
10.273515327901057
mean_absolute_error
0.2760155460898229
mean_absolute_error
0.2761099581149735
mean_absolute_error
0.2759603579138486
mean_absolute_error
0.27602055330443415
mean_absolute_error
0.27615838436234713
mean_absolute_error
0.2760668393553163
mean_absolute_error
0.27601545862649857
mean_absolute_error
0.27602956222588854
mean_absolute_error
0.27606674083405225
mean_absolute_error
0.2760358682458709
mean_prior_absolute_error
0.272904982835389
mean_prior_absolute_error
0.272904982835389
mean_prior_absolute_error
0.272904982835389
mean_prior_absolute_error
0.272904982835389
mean_prior_absolute_error
0.272804289453111
mean_prior_absolute_error
0.27287651677373237
mean_prior_absolute_error
0.2728747259382053
mean_prior_absolute_error
0.2728747259382053
mean_prior_absolute_error
0.2728747259382053
mean_prior_absolute_error
0.2728747259382053
number_of_instances
280 [58,34,68,51,41,28]
number_of_instances
280 [58,34,68,51,41,28]
number_of_instances
280 [58,34,68,51,41,28]
number_of_instances
280 [58,34,68,51,41,28]
number_of_instances
280 [58,34,68,52,41,27]
number_of_instances
280 [58,35,68,51,41,27]
number_of_instances
279 [57,34,68,51,42,27]
number_of_instances
279 [57,34,68,51,42,27]
number_of_instances
279 [57,34,68,51,42,27]
number_of_instances
279 [57,34,68,51,42,27]
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24285714285714285
predictive_accuracy
0.24372759856630824
predictive_accuracy
0.24372759856630824
predictive_accuracy
0.24372759856630824
predictive_accuracy
0.24372759856630824
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
prior_entropy
2.5206634795042744
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24285714285714285 [0,0,1,0,0,0]
recall
0.24372759856630824 [0,0,1,0,0,0]
recall
0.24372759856630824 [0,0,1,0,0,0]
recall
0.24372759856630824 [0,0,1,0,0,0]
recall
0.24372759856630824 [0,0,1,0,0,0]
relative_absolute_error
1.0113979716387596
relative_absolute_error
1.011743923640697
relative_absolute_error
1.0111957467640031
relative_absolute_error
1.011416319470152
relative_absolute_error
1.0122948759931893
relative_absolute_error
1.011691451574154
relative_absolute_error
1.0115097969498448
relative_absolute_error
1.0115614822033672
relative_absolute_error
1.0116977301026033
relative_absolute_error
1.01158459178217
root_mean_prior_squared_error
0.36940459271455434
root_mean_prior_squared_error
0.36940459271455434
root_mean_prior_squared_error
0.36940459271455434
root_mean_prior_squared_error
0.36940459271455434
root_mean_prior_squared_error
0.36926827610333357
root_mean_prior_squared_error
0.36936606105183667
root_mean_prior_squared_error
0.3693636368423697
root_mean_prior_squared_error
0.3693636368423697
root_mean_prior_squared_error
0.3693636368423697
root_mean_prior_squared_error
0.3693636368423697
root_mean_squared_error
0.3705076332040129
root_mean_squared_error
0.3706327735407058
root_mean_squared_error
0.3704389969195741
root_mean_squared_error
0.3705232581001053
root_mean_squared_error
0.37071723418216407
root_mean_squared_error
0.37058076757960073
root_mean_squared_error
0.37051412859239713
root_mean_squared_error
0.3705384939945349
root_mean_squared_error
0.3705804008380578
root_mean_squared_error
0.37053820952276395
root_relative_squared_error
1.0029859956026885
root_relative_squared_error
1.003324757868131
root_relative_squared_error
1.0028001931362533
root_relative_squared_error
1.0030282931171226
root_relative_squared_error
1.0039238628731406
root_relative_squared_error
1.00328862517662
root_relative_squared_error
1.0031147942982768
root_relative_squared_error
1.0031807601912544
root_relative_squared_error
1.0032942170650312
root_relative_squared_error
1.0031799900240193
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
1339.5688450036687
usercpu_time_millis
1308.165515998553
usercpu_time_millis
1289.0291410003556
usercpu_time_millis
1282.2335250020842
usercpu_time_millis
1280.0997470003495
usercpu_time_millis
1305.975497001782
usercpu_time_millis
1290.1439699999173
usercpu_time_millis
1315.8818660049292
usercpu_time_millis
1329.1815060001682
usercpu_time_millis
1281.7878860005294
usercpu_time_millis_testing
3.7520660007430706
usercpu_time_millis_testing
3.7629090002155863
usercpu_time_millis_testing
3.728792999027064
usercpu_time_millis_testing
3.6670369991043117
usercpu_time_millis_testing
3.772184001718415
usercpu_time_millis_testing
3.630338000220945
usercpu_time_millis_testing
3.8072520001151133
usercpu_time_millis_testing
3.7703420020989142
usercpu_time_millis_testing
3.8194919980014674
usercpu_time_millis_testing
3.686842999741202
usercpu_time_millis_training
1335.8167790029256
usercpu_time_millis_training
1304.4026069983374
usercpu_time_millis_training
1285.3003480013285
usercpu_time_millis_training
1278.56648800298
usercpu_time_millis_training
1276.327562998631
usercpu_time_millis_training
1302.3451590015611
usercpu_time_millis_training
1286.3367179998022
usercpu_time_millis_training
1312.1115240028303
usercpu_time_millis_training
1325.3620140021667
usercpu_time_millis_training
1278.1010430007882