10585116
28997
Marc Boel
9967
Supervised Classification
19039
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(2)
8301398
Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1.
n_jobs
null
19031
remainder
"drop"
19031
sparse_threshold
0.3
19031
transformer_weights
null
19031
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}]
19031
verbose
false
19031
verbose_feature_names_out
true
19031
add_indicator
false
19032
copy
true
19032
fill_value
null
19032
missing_values
NaN
19032
strategy
"median"
19032
verbose
0
19032
categories
"auto"
19033
drop
null
19033
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
19033
handle_unknown
"ignore"
19033
sparse
true
19033
memory
null
19039
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}]
19039
verbose
false
19039
ccp_alpha
0.0
19040
criterion
"friedman_mse"
19040
init
null
19040
learning_rate
0.042869239518196114
19040
loss
"deviance"
19040
max_depth
3
19040
max_features
null
19040
max_leaf_nodes
780
19040
min_impurity_decrease
0.0
19040
min_samples_leaf
116
19040
min_samples_split
2
19040
min_weight_fraction_leaf
0.0
19040
n_estimators
100
19040
n_iter_no_change
14
19040
random_state
59548
19040
subsample
1.0
19040
tol
0.0001
19040
validation_fraction
0.2497271074646948
19040
verbose
0
19040
warm_start
false
19040
openml-python
Sklearn_1.0.1.
1504
steel-plates-fault
https://www.openml.org/data/download/1592296/php9xWOpn
-1
22096500
description
https://api.openml.org/data/download/22096500/description.xml
-1
22096501
predictions
https://api.openml.org/data/download/22096501/predictions.arff
area_under_roc_curve
0.9717717175788995 [0.971772,0.971772]
average_cost
0
f_measure
0.913553400039378 [0.932156,0.878505]
kappa
0.8107710226056718
kb_relative_information_score
0.6228437930972021
mean_absolute_error
0.18617652799454798
mean_prior_absolute_error
0.45306405137877787
weighted_recall
0.9129314786192684 [0.915615,0.907875]
number_of_instances
1941 [1268,673]
precision
0.9152111553744376 [0.949305,0.850975]
predictive_accuracy
0.9129314786192684
prior_entropy
0.9311124141243181
relative_absolute_error
0.4109276104073366
root_mean_prior_squared_error
0.47592842871248736
root_mean_squared_error
0.2639791037117185
root_relative_squared_error
0.554661347769983
total_cost
0
unweighted_recall
0.9117451638456743 [0.915615,0.907875]
area_under_roc_curve
0.977999073645206 [0.977999,0.977999]
area_under_roc_curve
0.9696204019273709 [0.96962,0.96962]
area_under_roc_curve
0.9724997061934423 [0.9725,0.9725]
area_under_roc_curve
0.9737924550475967 [0.973792,0.973792]
area_under_roc_curve
0.9722646609472322 [0.972265,0.972265]
area_under_roc_curve
0.9582794687977436 [0.958279,0.958279]
area_under_roc_curve
0.9737336937360442 [0.973734,0.973734]
area_under_roc_curve
0.9593371724056879 [0.959337,0.959337]
area_under_roc_curve
0.978874883286648 [0.978875,0.978875]
area_under_roc_curve
0.9842436974789917 [0.984244,0.984244]
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
0.9388483516483517 [0.952,0.914286]
f_measure
0.918507946514052 [0.934959,0.887324]
f_measure
0.9335221178416848 [0.947791,0.906475]
f_measure
0.9011091785006914 [0.926641,0.852713]
f_measure
0.9025488834038516 [0.924303,0.861314]
f_measure
0.8728223175940406 [0.897959,0.825175]
f_measure
0.9083214398283086 [0.926829,0.873239]
f_measure
0.8929056997192899 [0.91498,0.851064]
f_measure
0.9286566015060184 [0.942623,0.902778]
f_measure
0.9379262466787743 [0.952756,0.910448]
kappa
0.866346812885538
kappa
0.8226082980912103
kappa
0.8543711745005197
kappa
0.7795190812298122
kappa
0.7856727526456565
kappa
0.7237726392527623
kappa
0.8004343353526117
kappa
0.7663722904002753
kappa
0.8456818181818182
kappa
0.863219741480611
kb_relative_information_score
0.6451379111872526
kb_relative_information_score
0.6276372527356255
kb_relative_information_score
0.6291680886910269
kb_relative_information_score
0.623530861270286
kb_relative_information_score
0.6260401058211444
kb_relative_information_score
0.5654376315298093
kb_relative_information_score
0.6285849536397544
kb_relative_information_score
0.5679890678804224
kb_relative_information_score
0.6448692921112614
kb_relative_information_score
0.6695064005441206
mean_absolute_error
0.17834876814847472
mean_absolute_error
0.18345731638134208
mean_absolute_error
0.18444273760245075
mean_absolute_error
0.18519917190942095
mean_absolute_error
0.18424692604975915
mean_absolute_error
0.20944468361065263
mean_absolute_error
0.18134346527210518
mean_absolute_error
0.20885073432006465
mean_absolute_error
0.178239220598872
mean_absolute_error
0.1682326053298937
mean_prior_absolute_error
0.4536732781714767
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.4526452345453676
mean_prior_absolute_error
0.45422372672718864
mean_prior_absolute_error
0.45422372672718864
number_of_instances
195 [127,68]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [127,67]
number_of_instances
194 [126,68]
number_of_instances
194 [126,68]
precision
0.940073657146828 [0.96748,0.888889]
precision
0.9227375898813134 [0.966387,0.84]
precision
0.9353663173905695 [0.967213,0.875]
precision
0.9014949965232638 [0.909091,0.887097]
precision
0.9034942277542876 [0.935484,0.842857]
precision
0.8783659196041826 [0.932203,0.776316]
precision
0.9126316093447688 [0.957983,0.826667]
precision
0.896474180365933 [0.941667,0.810811]
precision
0.9327551799295548 [0.974576,0.855263]
precision
0.9379271126210559 [0.945312,0.924242]
predictive_accuracy
0.9384615384615383
predictive_accuracy
0.9175257731958762
predictive_accuracy
0.9329896907216495
predictive_accuracy
0.9020618556701031
predictive_accuracy
0.9020618556701031
predictive_accuracy
0.8711340206185567
predictive_accuracy
0.9072164948453608
predictive_accuracy
0.8917525773195877
predictive_accuracy
0.9278350515463917
predictive_accuracy
0.9381443298969071
prior_entropy
0.932928534004902
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9298639109616103
prior_entropy
0.9345694345320188
prior_entropy
0.9345694345320188
relative_absolute_error
0.39312160695755927
relative_absolute_error
0.40530044807741056
relative_absolute_error
0.4074774757933842
relative_absolute_error
0.4091486174496749
relative_absolute_error
0.4070448819257203
relative_absolute_error
0.46271266684386236
relative_absolute_error
0.4006304527965367
relative_absolute_error
0.46140049288231716
relative_absolute_error
0.3924040293604572
relative_absolute_error
0.3703738828045324
root_mean_prior_squared_error
0.4765680392655914
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.47548822532565527
root_mean_prior_squared_error
0.4771452028525092
root_mean_prior_squared_error
0.4771452028525092
root_mean_squared_error
0.25117384886584265
root_mean_squared_error
0.26333351749514644
root_mean_squared_error
0.2604051300751748
root_mean_squared_error
0.26474880671858847
root_mean_squared_error
0.2640693252243658
root_mean_squared_error
0.28933749568996536
root_mean_squared_error
0.26289939246376703
root_mean_squared_error
0.28676977514917823
root_mean_squared_error
0.2538474813525015
root_mean_squared_error
0.23939034222391434
root_relative_squared_error
0.5270471961420465
root_relative_squared_error
0.5538171156915462
root_relative_squared_error
0.5476584197154976
root_relative_squared_error
0.5567936125805548
root_relative_squared_error
0.5553645940307111
root_relative_squared_error
0.6085061212437008
root_relative_squared_error
0.5529041066867868
root_relative_squared_error
0.6031059443223302
root_relative_squared_error
0.5320130640210347
root_relative_squared_error
0.5017138195936396
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
0.9390921723019916 [0.937008,0.941176]
unweighted_recall
0.9229051592431543 [0.905512,0.940299]
unweighted_recall
0.9347161828652015 [0.929134,0.940299]
unweighted_recall
0.8828887060759196 [0.944882,0.820896]
unweighted_recall
0.8969914208485134 [0.913386,0.880597]
unweighted_recall
0.8733693736044188 [0.866142,0.880597]
unweighted_recall
0.9115054648019744 [0.897638,0.925373]
unweighted_recall
0.8926430837936303 [0.889764,0.895522]
unweighted_recall
0.9342903828197946 [0.912698,0.955882]
unweighted_recall
0.9286881419234361 [0.960317,0.897059]
usercpu_time_millis
1005.0306210014242
usercpu_time_millis
1005.6357260000368
usercpu_time_millis
1002.0778060006705
usercpu_time_millis
999.4904449995374
usercpu_time_millis
1007.0080530003906
usercpu_time_millis
1005.2992090004409
usercpu_time_millis
1017.2423280000658
usercpu_time_millis
1014.2504620016553
usercpu_time_millis
1003.9179889972729
usercpu_time_millis
989.5324629997049
usercpu_time_millis_testing
6.736262001140858
usercpu_time_millis_testing
7.141505999243236
usercpu_time_millis_testing
6.887916000778205
usercpu_time_millis_testing
7.251807999637094
usercpu_time_millis_testing
7.4511020011414075
usercpu_time_millis_testing
7.562857999801054
usercpu_time_millis_testing
6.576812000275822
usercpu_time_millis_testing
7.2323630010942
usercpu_time_millis_testing
7.18758399852959
usercpu_time_millis_testing
4.552933998638764
usercpu_time_millis_training
998.2943590002833
usercpu_time_millis_training
998.4942200007936
usercpu_time_millis_training
995.1898899998923
usercpu_time_millis_training
992.2386369999003
usercpu_time_millis_training
999.5569509992492
usercpu_time_millis_training
997.7363510006398
usercpu_time_millis_training
1010.6655159997899
usercpu_time_millis_training
1007.018099000561
usercpu_time_millis_training
996.7304049987433
usercpu_time_millis_training
984.9795290010661
wall_clock_time_millis
1027.5375843048096
wall_clock_time_millis
1033.212661743164
wall_clock_time_millis
1008.9213848114014
wall_clock_time_millis
1023.6086845397949
wall_clock_time_millis
1011.458158493042
wall_clock_time_millis
1031.6689014434814
wall_clock_time_millis
1037.5034809112549
wall_clock_time_millis
1037.8758907318115
wall_clock_time_millis
1008.4662437438965
wall_clock_time_millis
1014.533281326294
wall_clock_time_millis_testing
6.742238998413086
wall_clock_time_millis_testing
9.047746658325195
wall_clock_time_millis_testing
6.893634796142578
wall_clock_time_millis_testing
7.323741912841797
wall_clock_time_millis_testing
7.459163665771484
wall_clock_time_millis_testing
7.568120956420898
wall_clock_time_millis_testing
6.582736968994141
wall_clock_time_millis_testing
7.251262664794922
wall_clock_time_millis_testing
7.308721542358398
wall_clock_time_millis_testing
4.557371139526367
wall_clock_time_millis_training
1020.7953453063965
wall_clock_time_millis_training
1024.1649150848389
wall_clock_time_millis_training
1002.0277500152588
wall_clock_time_millis_training
1016.2849426269531
wall_clock_time_millis_training
1003.9989948272705
wall_clock_time_millis_training
1024.1007804870605
wall_clock_time_millis_training
1030.9207439422607
wall_clock_time_millis_training
1030.6246280670166
wall_clock_time_millis_training
1001.1575222015381
wall_clock_time_millis_training
1009.9759101867676
weighted_recall
0.9384615384615385 [0.937008,0.941176]
weighted_recall
0.9175257731958762 [0.905512,0.940299]
weighted_recall
0.9329896907216495 [0.929134,0.940299]
weighted_recall
0.9020618556701031 [0.944882,0.820896]
weighted_recall
0.9020618556701031 [0.913386,0.880597]
weighted_recall
0.8711340206185567 [0.866142,0.880597]
weighted_recall
0.9072164948453608 [0.897638,0.925373]
weighted_recall
0.8917525773195877 [0.889764,0.895522]
weighted_recall
0.9278350515463918 [0.912698,0.955882]
weighted_recall
0.9381443298969072 [0.960317,0.897059]