10559564
8323
Heinrich Peters
14954
Supervised Classification
18298
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4)
8276176
copy
true
17405
with_mean
true
17405
with_std
true
17405
add_indicator
false
17407
copy
true
17407
fill_value
null
17407
missing_values
NaN
17407
strategy
"most_frequent"
17407
verbose
0
17407
categorical_features
null
17408
categories
null
17408
drop
null
17408
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
17408
handle_unknown
"ignore"
17408
n_values
null
17408
sparse
true
17408
C
1.2019329859336583
17495
cache_size
200
17495
class_weight
null
17495
coef0
-0.8056274588169823
17495
decision_function_shape
"ovr"
17495
degree
2
17495
gamma
0.14660663245874161
17495
kernel
"rbf"
17495
max_iter
-1
17495
probability
true
17495
random_state
1
17495
shrinking
true
17495
tol
0.001
17495
verbose
false
17495
memory
null
18298
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
18298
verbose
false
18298
n_jobs
null
18299
remainder
"drop"
18299
sparse_threshold
0.3
18299
transformer_weights
null
18299
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, true]}}]
18299
verbose
false
18299
memory
null
18300
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18300
verbose
false
18300
memory
null
18301
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
18301
verbose
false
18301
openml-python
Sklearn_0.21.2.
6332
cylinder-bands
https://www.openml.org/data/download/1854224/phpAz9Len
-1
22044115
description
https://api.openml.org/data/download/22044115/description.xml
-1
22044116
predictions
https://api.openml.org/data/download/22044116/predictions.arff
area_under_roc_curve
0.8852760908681961 [0.885276,0.885276]
average_cost
0
f_measure
0.8157005525214781 [0.77551,0.84507]
kappa
0.6208833290783763
kb_relative_information_score
0.4703727395877963
mean_absolute_error
0.2726122704273149
mean_prior_absolute_error
0.48794587945879536
weighted_recall
0.8166666666666667 [0.75,0.865385]
number_of_instances
540 [228,312]
precision
0.816031356333721 [0.802817,0.825688]
predictive_accuracy
0.8166666666666668
prior_entropy
0.9824743303740947
relative_absolute_error
0.5586936623579699
root_mean_prior_squared_error
0.49391365607219145
root_mean_squared_error
0.36556669691472815
root_relative_squared_error
0.7401429225947463
total_cost
0
unweighted_recall
0.8076923076923077 [0.75,0.865385]
area_under_roc_curve
0.9130434782608695 [0.913043,0.913043]
area_under_roc_curve
0.9368863955119214 [0.936886,0.936886]
area_under_roc_curve
0.9158485273492287 [0.915849,0.915849]
area_under_roc_curve
0.758765778401122 [0.758766,0.758766]
area_under_roc_curve
0.8611500701262272 [0.86115,0.86115]
area_under_roc_curve
0.8260869565217391 [0.826087,0.826087]
area_under_roc_curve
0.932678821879383 [0.932679,0.932679]
area_under_roc_curve
0.8920056100981767 [0.892006,0.892006]
area_under_roc_curve
0.9659090909090908 [0.965909,0.965909]
area_under_roc_curve
0.8480113636363638 [0.848011,0.848011]
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
0.8888888888888888 [0.869565,0.903226]
f_measure
0.8524691358024691 [0.833333,0.866667]
f_measure
0.8116081449414784 [0.761905,0.848485]
f_measure
0.7564168819982774 [0.697674,0.8]
f_measure
0.7761994949494949 [0.727273,0.8125]
f_measure
0.7362514029180696 [0.666667,0.787879]
f_measure
0.868839859537534 [0.837209,0.892308]
f_measure
0.8116081449414784 [0.761905,0.848485]
f_measure
0.9070430000662557 [0.883721,0.923077]
f_measure
0.7429012345679011 [0.708333,0.766667]
kappa
0.7727910238429172
kappa
0.7004160887656034
kappa
0.612625538020086
kappa
0.49928673323823125
kappa
0.5404255319148936
kappa
0.4576757532281205
kappa
0.7303851640513552
kappa
0.612625538020086
kappa
0.8068669527896997
kappa
0.47790055248618774
kb_relative_information_score
0.5739056645914444
kb_relative_information_score
0.5216963285824835
kb_relative_information_score
0.529100866605946
kb_relative_information_score
0.33770434636479885
kb_relative_information_score
0.4794056475414194
kb_relative_information_score
0.37039206125773555
kb_relative_information_score
0.524994533012664
kb_relative_information_score
0.4557223042291978
kb_relative_information_score
0.5432708940882418
kb_relative_information_score
0.3672785991005252
mean_absolute_error
0.22577332776884984
mean_absolute_error
0.24980106215083298
mean_absolute_error
0.2423593814490236
mean_absolute_error
0.33271254225687735
mean_absolute_error
0.2653443462605729
mean_absolute_error
0.3165852271410878
mean_absolute_error
0.2482417845652894
mean_absolute_error
0.28310668337719286
mean_absolute_error
0.24493332009535834
mean_absolute_error
0.3172650292080647
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.4856498564985656
mean_prior_absolute_error
0.4856498564985656
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [22,32]
number_of_instances
54 [22,32]
precision
0.8888888888888888 [0.869565,0.903226]
precision
0.8554278416347382 [0.8,0.896552]
precision
0.8179337231968811 [0.842105,0.8]
precision
0.7584422657952069 [0.75,0.764706]
precision
0.7768157768157766 [0.761905,0.787879]
precision
0.7402951824004455 [0.736842,0.742857]
precision
0.8729847494553377 [0.9,0.852941]
precision
0.8179337231968811 [0.842105,0.8]
precision
0.9073272406605739 [0.904762,0.909091]
precision
0.7531542531542532 [0.653846,0.821429]
predictive_accuracy
0.8888888888888888
predictive_accuracy
0.8518518518518519
predictive_accuracy
0.8148148148148148
predictive_accuracy
0.7592592592592592
predictive_accuracy
0.7777777777777777
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.8703703703703703
predictive_accuracy
0.8148148148148148
predictive_accuracy
0.9074074074074074
predictive_accuracy
0.7407407407407408
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9757955887617137
prior_entropy
0.9757955887617137
relative_absolute_error
0.46215790719951655
relative_absolute_error
0.5113426693964589
relative_absolute_error
0.49610955212267543
relative_absolute_error
0.6810624343806317
relative_absolute_error
0.5431597654465267
relative_absolute_error
0.6480498271062628
relative_absolute_error
0.5081508288331851
relative_absolute_error
0.5795192620704763
relative_absolute_error
0.5043413826193146
relative_absolute_error
0.6532793636458157
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.4915838450298872
root_mean_prior_squared_error
0.4915838450298872
root_mean_squared_error
0.32920781452950276
root_mean_squared_error
0.32601182560363856
root_mean_squared_error
0.3396060126220193
root_mean_squared_error
0.4438129756552796
root_mean_squared_error
0.3745048293874879
root_mean_squared_error
0.4150966925622921
root_mean_squared_error
0.327891567001283
root_mean_squared_error
0.3672574563720215
root_mean_squared_error
0.30453727724819324
root_mean_squared_error
0.40216091128535403
root_relative_squared_error
0.6657463031488207
root_relative_squared_error
0.6592831582342943
root_relative_squared_error
0.6867742424442338
root_relative_squared_error
0.897508609430354
root_relative_squared_error
0.7573489895202837
root_relative_squared_error
0.8394366000017379
root_relative_squared_error
0.6630844983942967
root_relative_squared_error
0.7426928617504039
root_relative_squared_error
0.6195022076644484
root_relative_squared_error
0.8180922041099693
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
unweighted_recall
0.8863955119214586 [0.869565,0.903226]
unweighted_recall
0.8541374474053296 [0.869565,0.83871]
unweighted_recall
0.7994389901823282 [0.695652,0.903226]
unweighted_recall
0.7454417952314165 [0.652174,0.83871]
unweighted_recall
0.7671809256661992 [0.695652,0.83871]
unweighted_recall
0.723702664796634 [0.608696,0.83871]
unweighted_recall
0.8590462833099579 [0.782609,0.935484]
unweighted_recall
0.7994389901823282 [0.695652,0.903226]
unweighted_recall
0.9005681818181819 [0.863636,0.9375]
unweighted_recall
0.7457386363636364 [0.772727,0.71875]
usercpu_time_millis
286.61399999998594
usercpu_time_millis
288.5699999999929
usercpu_time_millis
288.0260000000021
usercpu_time_millis
284.78199999995013
usercpu_time_millis
280.0039999999626
usercpu_time_millis
279.0780000000268
usercpu_time_millis
277.11800000002995
usercpu_time_millis
279.3839999999932
usercpu_time_millis
287.38399999997455
usercpu_time_millis
301.21400000001586
usercpu_time_millis_testing
11.140000000011696
usercpu_time_millis_testing
11.368000000004486
usercpu_time_millis_testing
11.0779999999977
usercpu_time_millis_testing
12.465999999960786
usercpu_time_millis_testing
12.107999999955155
usercpu_time_millis_testing
11.797999999998865
usercpu_time_millis_testing
10.632000000043718
usercpu_time_millis_testing
11.213999999995394
usercpu_time_millis_testing
11.002000000019052
usercpu_time_millis_testing
14.972000000000207
usercpu_time_millis_training
275.47399999997424
usercpu_time_millis_training
277.2019999999884
usercpu_time_millis_training
276.9480000000044
usercpu_time_millis_training
272.31599999998934
usercpu_time_millis_training
267.89600000000746
usercpu_time_millis_training
267.28000000002794
usercpu_time_millis_training
266.48599999998623
usercpu_time_millis_training
268.1699999999978
usercpu_time_millis_training
276.3819999999555
usercpu_time_millis_training
286.24200000001565
wall_clock_time_millis
145.27392387390137
wall_clock_time_millis
145.63775062561035
wall_clock_time_millis
146.21806144714355
wall_clock_time_millis
150.61116218566895
wall_clock_time_millis
141.035795211792
wall_clock_time_millis
140.31457901000977
wall_clock_time_millis
139.2369270324707
wall_clock_time_millis
140.3181552886963
wall_clock_time_millis
145.53499221801758
wall_clock_time_millis
151.5359878540039
wall_clock_time_millis_testing
5.587100982666016
wall_clock_time_millis_testing
5.699872970581055
wall_clock_time_millis_testing
5.689859390258789
wall_clock_time_millis_testing
6.365060806274414
wall_clock_time_millis_testing
6.247043609619141
wall_clock_time_millis_testing
5.963802337646484
wall_clock_time_millis_testing
5.321025848388672
wall_clock_time_millis_testing
5.685091018676758
wall_clock_time_millis_testing
5.529880523681641
wall_clock_time_millis_testing
7.513999938964844
wall_clock_time_millis_training
139.68682289123535
wall_clock_time_millis_training
139.9378776550293
wall_clock_time_millis_training
140.52820205688477
wall_clock_time_millis_training
144.24610137939453
wall_clock_time_millis_training
134.78875160217285
wall_clock_time_millis_training
134.35077667236328
wall_clock_time_millis_training
133.91590118408203
wall_clock_time_millis_training
134.63306427001953
wall_clock_time_millis_training
140.00511169433594
wall_clock_time_millis_training
144.02198791503906
weighted_recall
0.8888888888888888 [0.869565,0.903226]
weighted_recall
0.8518518518518519 [0.869565,0.83871]
weighted_recall
0.8148148148148148 [0.695652,0.903226]
weighted_recall
0.7592592592592593 [0.652174,0.83871]
weighted_recall
0.7777777777777778 [0.695652,0.83871]
weighted_recall
0.7407407407407407 [0.608696,0.83871]
weighted_recall
0.8703703703703703 [0.782609,0.935484]
weighted_recall
0.8148148148148148 [0.695652,0.903226]
weighted_recall
0.9074074074074074 [0.863636,0.9375]
weighted_recall
0.7407407407407407 [0.772727,0.71875]