10221043
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)
8146475
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
"mean"
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
0.04439226704471478
9667
loss
"deviance"
9667
max_depth
30
9667
max_features
0.275173174310007
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.09741712240446332
9667
min_impurity_split
null
9667
min_samples_leaf
7
9667
min_samples_split
11
9667
min_weight_fraction_leaf
0.3741118867093155
9667
n_estimators
278
9667
n_iter_no_change
1819
9667
presort
"auto"
9667
random_state
23372
9667
subsample
0.6485633797324869
9667
tol
0.002257981555704155
9667
validation_fraction
0.8473478323751332
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
21363002
description
https://api.openml.org/data/download/21363002/description.xml
-1
21363003
predictions
https://api.openml.org/data/download/21363003/predictions.arff
area_under_roc_curve
0.6344048450032261 [0.62141,0.608908,0.624101,0.502872,0.749933,0.789774]
average_cost
0
f_measure
0.19792443011201882 [0.060976,0.064516,0.434035,0.010791,0.232558,0.362545]
kappa
0.10660427128345426
kb_relative_information_score
379.1498677790329
mean_absolute_error
0.2604143241284335
mean_prior_absolute_error
0.27287997162595995
number_of_instances
2796 [576,341,680,511,414,274]
precision
0.22520541259951493 [0.25,0.209677,0.306618,0.066667,0.235732,0.270125]
predictive_accuracy
0.2814735336194564
prior_entropy
2.5206634795042744
recall
0.2814735336194564 [0.034722,0.038123,0.742647,0.005871,0.229469,0.551095]
relative_absolute_error
0.9543182028961317
root_mean_prior_squared_error
0.3693707377543301
root_mean_squared_error
0.3612965290977436
root_relative_squared_error
0.9781406380330089
total_cost
0
area_under_roc_curve
0.6426354250949771 [0.640805,0.607604,0.66284,0.464381,0.733136,0.832058]
area_under_roc_curve
0.6200316445244896 [0.603604,0.634326,0.569575,0.481334,0.737167,0.840349]
area_under_roc_curve
0.6478145824993162 [0.721536,0.54627,0.605855,0.500771,0.785284,0.786848]
area_under_roc_curve
0.622811376664521 [0.61269,0.472143,0.594686,0.568114,0.767782,0.782384]
area_under_roc_curve
0.6146123959897337 [0.601041,0.685856,0.58109,0.490806,0.686601,0.767604]
area_under_roc_curve
0.6446733587928268 [0.592847,0.677668,0.659267,0.501627,0.754261,0.780266]
area_under_roc_curve
0.6498540445160081 [0.571914,0.523709,0.74662,0.539345,0.800934,0.703263]
area_under_roc_curve
0.6447720886167161 [0.652323,0.605042,0.642354,0.479317,0.742214,0.845899]
area_under_roc_curve
0.6414883299555763 [0.598743,0.659784,0.626812,0.514577,0.788075,0.757349]
area_under_roc_curve
0.6509000426978427 [0.621701,0.669928,0.662845,0.456828,0.778983,0.825838]
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
0.21838402226423892 [0.186047,0,0.447489,0.036364,0.164384,0.404762]
f_measure
0.20056282868762854 [0.153846,0.1,0.373206,0,0.16092,0.423529]
f_measure
0.19695104988807755 [0.105263,0,0.439462,0,0.222222,0.372093]
f_measure
0.18421597070908635 [0,0.042553,0.422907,0.070175,0.225,0.302326]
kappa
0.1172090370417314
kappa
0.08219868885526975
kappa
0.07734228953455212
kappa
0.11524659404871544
kappa
0.07552436398436879
kappa
0.10516240289841317
kappa
0.1469656193767218
kappa
0.13397236920404657
kappa
0.08574064647493003
kappa
0.12643106022896963
kb_relative_information_score
38.091382945867764
kb_relative_information_score
36.20613873089532
kb_relative_information_score
39.59110600915982
kb_relative_information_score
38.785580466527776
kb_relative_information_score
35.868935036660645
kb_relative_information_score
40.238440335026176
kb_relative_information_score
38.4025718413981
kb_relative_information_score
38.71393992577926
kb_relative_information_score
34.916211800296075
kb_relative_information_score
38.33556068742232
mean_absolute_error
0.25959340407584924
mean_absolute_error
0.26211662013613884
mean_absolute_error
0.2590361873432007
mean_absolute_error
0.25978186321509017
mean_absolute_error
0.26198991529206206
mean_absolute_error
0.2589601705233237
mean_absolute_error
0.260210541438016
mean_absolute_error
0.26006013278145895
mean_absolute_error
0.26206921217156426
mean_absolute_error
0.26032880643731776
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]
precision
0.24133983477496956 [0.285714,0,0.324503,0.25,0.1875,0.303571]
precision
0.2236538559627561 [0.3,0.333333,0.276596,0,0.152174,0.315789]
precision
0.18190248921693702 [0.222222,0,0.316129,0,0.225,0.271186]
precision
0.20086095865807377 [0,0.076923,0.301887,0.333333,0.236842,0.220339]
predictive_accuracy
0.28928571428571426
predictive_accuracy
0.2571428571428572
predictive_accuracy
0.2571428571428572
predictive_accuracy
0.28928571428571426
predictive_accuracy
0.26071428571428573
predictive_accuracy
0.2785714285714286
predictive_accuracy
0.3118279569892473
predictive_accuracy
0.3082437275985663
predictive_accuracy
0.2616487455197133
predictive_accuracy
0.3010752688172043
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
0.2892857142857143 [0.137931,0,0.720588,0.019608,0.146341,0.607143]
recall
0.2571428571428571 [0.103448,0.058824,0.573529,0,0.170732,0.642857]
recall
0.2571428571428571 [0,0.029412,0.720588,0,0.146341,0.571429]
recall
0.2892857142857143 [0,0.029412,0.75,0,0.243902,0.678571]
recall
0.26071428571428573 [0,0,0.705882,0,0.243902,0.555556]
recall
0.2785714285714286 [0.068966,0,0.720588,0,0.219512,0.592593]
recall
0.3118279569892473 [0.035088,0.205882,0.852941,0,0.261905,0.333333]
recall
0.30824372759856633 [0,0.029412,0.823529,0,0.380952,0.481481]
recall
0.2616487455197133 [0,0.029412,0.705882,0.039216,0.214286,0.481481]
recall
0.3010752688172043 [0,0,0.852941,0,0.261905,0.555556]
relative_absolute_error
0.9512226613774618
relative_absolute_error
0.9604684290218422
relative_absolute_error
0.949180863800667
relative_absolute_error
0.9519132282453984
relative_absolute_error
0.9603584892938141
relative_absolute_error
0.9490013050043877
relative_absolute_error
0.9535897490812058
relative_absolute_error
0.9530385486868128
relative_absolute_error
0.9604011924171827
relative_absolute_error
0.9540231530870007
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
0.3606772413857771
root_mean_squared_error
0.3637734987786459
root_mean_squared_error
0.3605116632391289
root_mean_squared_error
0.36157892918562734
root_mean_squared_error
0.36500318437077345
root_mean_squared_error
0.3608045565412257
root_mean_squared_error
0.3604146125848585
root_mean_squared_error
0.3594759309288738
root_mean_squared_error
0.3615977273557381
root_mean_squared_error
0.3590694758491397
root_relative_squared_error
0.9763745456854105
root_relative_squared_error
0.9847562968978578
root_relative_squared_error
0.9759263158855821
root_relative_squared_error
0.978815467692428
root_relative_squared_error
0.9884498831647087
root_relative_squared_error
0.976821085060629
root_relative_squared_error
0.9757717778230284
root_relative_squared_error
0.9732304295083719
root_relative_squared_error
0.9789748943533771
root_relative_squared_error
0.9721300096532696
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
1330.1142759955837
usercpu_time_millis
1245.3050450021692
usercpu_time_millis
1229.9447910008894
usercpu_time_millis
1242.5128659997426
usercpu_time_millis
1230.5501789996924
usercpu_time_millis
1221.9932890002383
usercpu_time_millis
1220.5955919998814
usercpu_time_millis
1222.6927449992218
usercpu_time_millis
1213.8482080044923
usercpu_time_millis
1222.1700130030513
usercpu_time_millis_testing
4.04184499711846
usercpu_time_millis_testing
4.005246999440715
usercpu_time_millis_testing
3.9769880022504367
usercpu_time_millis_testing
4.182587999821408
usercpu_time_millis_testing
4.0014400001382455
usercpu_time_millis_testing
3.9828709996072575
usercpu_time_millis_testing
3.9785240005585365
usercpu_time_millis_testing
3.857818999676965
usercpu_time_millis_testing
3.959094003221253
usercpu_time_millis_testing
3.870026001095539
usercpu_time_millis_training
1326.0724309984653
usercpu_time_millis_training
1241.2997980027285
usercpu_time_millis_training
1225.967802998639
usercpu_time_millis_training
1238.3302779999212
usercpu_time_millis_training
1226.5487389995542
usercpu_time_millis_training
1218.010418000631
usercpu_time_millis_training
1216.617067999323
usercpu_time_millis_training
1218.8349259995448
usercpu_time_millis_training
1209.889114001271
usercpu_time_millis_training
1218.2999870019557