10585067
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)
8301349
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
"most_frequent"
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
0.46750728605561914
19040
loss
"deviance"
19040
max_depth
3
19040
max_features
null
19040
max_leaf_nodes
227
19040
min_impurity_decrease
0.0
19040
min_samples_leaf
42
19040
min_samples_split
2
19040
min_weight_fraction_leaf
0.0
19040
n_estimators
100
19040
n_iter_no_change
6
19040
random_state
30652
19040
subsample
1.0
19040
tol
0.0001
19040
validation_fraction
0.17139112918014396
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
22096402
description
https://api.openml.org/data/download/22096402/description.xml
-1
22096403
predictions
https://api.openml.org/data/download/22096403/predictions.arff
area_under_roc_curve
0.9997773517514214 [0.999777,0.999777]
average_cost
0
f_measure
0.9943377073785328 [0.995654,0.991858]
kappa
0.9875118660960412
kb_relative_information_score
0.9855647583984017
mean_absolute_error
0.0067282804552854705
mean_prior_absolute_error
0.45306405137877787
weighted_recall
0.994332818134982 [0.993691,0.995542]
number_of_instances
1941 [1268,673]
precision
0.9943570945726876 [0.997625,0.988201]
predictive_accuracy
0.994332818134982
prior_entropy
0.9311124141243181
relative_absolute_error
0.014850616452154543
root_mean_prior_squared_error
0.47592842871248736
root_mean_squared_error
0.06088655348151957
root_relative_squared_error
0.12793216334278212
total_cost
0
unweighted_recall
0.9946165997159477 [0.993691,0.995542]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.9996474321306853 [0.999647,0.999647]
area_under_roc_curve
0.9985897285227406 [0.99859,0.99859]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
1 [1,1]
area_under_roc_curve
0.998249299719888 [0.998249,0.998249]
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
1 [1,1]
f_measure
1 [1,1]
f_measure
1 [1,1]
f_measure
1 [1,1]
f_measure
1 [1,1]
f_measure
0.9845627951410111 [0.988142,0.977778]
f_measure
0.979451230664087 [0.984127,0.970588]
f_measure
0.9897256153320434 [0.992063,0.985294]
f_measure
1 [1,1]
f_measure
0.9896907216494846 [0.992063,0.985294]
kappa
1
kappa
1
kappa
1
kappa
1
kappa
1
kappa
0.9659210680407543
kappa
0.9547205041428404
kappa
0.9773602520714203
kappa
1
kappa
0.977357609710551
kb_relative_information_score
0.9999526329909323
kb_relative_information_score
0.9999524170932077
kb_relative_information_score
0.9999532589731901
kb_relative_information_score
0.9999547741669036
kb_relative_information_score
0.9999561465699713
kb_relative_information_score
0.9678324928659758
kb_relative_information_score
0.9542438284771364
kb_relative_information_score
0.9624622419168261
kb_relative_information_score
0.9999533487857949
kb_relative_information_score
0.9712641688800397
mean_absolute_error
0.0000306296585411977
mean_absolute_error
0.0000306681765691529
mean_absolute_error
0.00003012555894549952
mean_absolute_error
0.000029148999628375846
mean_absolute_error
0.000028264484662257792
mean_absolute_error
0.014102473704484543
mean_absolute_error
0.01989846198739258
mean_absolute_error
0.01899424146433562
mean_absolute_error
0.00003021982592366667
mean_absolute_error
0.014143094665550936
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
1 [1,1]
precision
1 [1,1]
precision
1 [1,1]
precision
1 [1,1]
precision
1 [1,1]
precision
0.984646779674069 [0.992063,0.970588]
precision
0.9797471985656655 [0.992,0.956522]
precision
0.9899895413118183 [1,0.971014]
precision
1 [1,1]
precision
0.9896907216494846 [0.992063,0.985294]
predictive_accuracy
1
predictive_accuracy
1
predictive_accuracy
1
predictive_accuracy
1
predictive_accuracy
1
predictive_accuracy
0.9845360824742267
predictive_accuracy
0.979381443298969
predictive_accuracy
0.9896907216494846
predictive_accuracy
1
predictive_accuracy
0.9896907216494846
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
0.000067514795371352
relative_absolute_error
0.00006775322974504683
relative_absolute_error
0.00006655445953331936
relative_absolute_error
0.00006439700985177237
relative_absolute_error
0.00006244290783409298
relative_absolute_error
0.03115568800508621
relative_absolute_error
0.04396039208802982
relative_absolute_error
0.041962755850977314
relative_absolute_error
0.0000665307075467174
relative_absolute_error
0.031136846961861638
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
0.00003283741549338191
root_mean_squared_error
0.000033334045521366966
root_mean_squared_error
0.00003329114557311315
root_mean_squared_error
0.000032304981630317445
root_mean_squared_error
0.00003092984008026352
root_mean_squared_error
0.08181894741435736
root_mean_squared_error
0.12308371528124185
root_mean_squared_error
0.08690576165832226
root_mean_squared_error
0.00003342381958595163
root_mean_squared_error
0.08771701164006811
root_relative_squared_error
0.0000689039398109566
root_relative_squared_error
0.00007010488114303345
root_relative_squared_error
0.00007001465819750324
root_relative_squared_error
0.0000679406553299868
root_relative_squared_error
0.00006504859307310944
root_relative_squared_error
0.17207355105022992
root_relative_squared_error
0.25885754625562707
root_relative_squared_error
0.18277163771784616
root_relative_squared_error
0.0000700495769131379
root_relative_squared_error
0.18383714457500766
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
1 [1,1]
unweighted_recall
1 [1,1]
unweighted_recall
1 [1,1]
unweighted_recall
1 [1,1]
unweighted_recall
1 [1,1]
unweighted_recall
0.9846632976848043 [0.984252,0.985075]
unweighted_recall
0.9807262898107886 [0.976378,0.985075]
unweighted_recall
0.9921259842519685 [0.984252,1]
unweighted_recall
1 [1,1]
unweighted_recall
0.9886788048552755 [0.992063,0.985294]
usercpu_time_millis
689.4269419990451
usercpu_time_millis
717.5239380012499
usercpu_time_millis
691.3230009995459
usercpu_time_millis
690.7924589995673
usercpu_time_millis
689.2701120013953
usercpu_time_millis
1029.3482489978487
usercpu_time_millis
1045.5373210006655
usercpu_time_millis
548.1575969988626
usercpu_time_millis
689.9761370004853
usercpu_time_millis
809.9323860005825
usercpu_time_millis_testing
6.941263000044273
usercpu_time_millis_testing
7.313135000003967
usercpu_time_millis_testing
6.472265000411426
usercpu_time_millis_testing
7.252506000440917
usercpu_time_millis_testing
7.085577000907506
usercpu_time_millis_testing
6.964885998968384
usercpu_time_millis_testing
6.698491999486578
usercpu_time_millis_testing
6.1376089997793315
usercpu_time_millis_testing
6.222419000550872
usercpu_time_millis_testing
4.505816999881063
usercpu_time_millis_training
682.4856789990008
usercpu_time_millis_training
710.210803001246
usercpu_time_millis_training
684.8507359991345
usercpu_time_millis_training
683.5399529991264
usercpu_time_millis_training
682.1845350004878
usercpu_time_millis_training
1022.3833629988803
usercpu_time_millis_training
1038.838829001179
usercpu_time_millis_training
542.0199879990832
usercpu_time_millis_training
683.7537179999345
usercpu_time_millis_training
805.4265690007014
wall_clock_time_millis
706.2399387359619
wall_clock_time_millis
742.9001331329346
wall_clock_time_millis
725.9185314178467
wall_clock_time_millis
724.8067855834961
wall_clock_time_millis
693.2566165924072
wall_clock_time_millis
1049.6978759765625
wall_clock_time_millis
1077.0528316497803
wall_clock_time_millis
552.6080131530762
wall_clock_time_millis
698.2741355895996
wall_clock_time_millis
815.1707649230957
wall_clock_time_millis_testing
6.947517395019531
wall_clock_time_millis_testing
7.323741912841797
wall_clock_time_millis_testing
6.479024887084961
wall_clock_time_millis_testing
7.25865364074707
wall_clock_time_millis_testing
7.093191146850586
wall_clock_time_millis_testing
6.970882415771484
wall_clock_time_millis_testing
6.704092025756836
wall_clock_time_millis_testing
6.1492919921875
wall_clock_time_millis_testing
6.22868537902832
wall_clock_time_millis_testing
4.511117935180664
wall_clock_time_millis_training
699.2924213409424
wall_clock_time_millis_training
735.5763912200928
wall_clock_time_millis_training
719.4395065307617
wall_clock_time_millis_training
717.548131942749
wall_clock_time_millis_training
686.1634254455566
wall_clock_time_millis_training
1042.726993560791
wall_clock_time_millis_training
1070.3487396240234
wall_clock_time_millis_training
546.4587211608887
wall_clock_time_millis_training
692.0454502105713
wall_clock_time_millis_training
810.659646987915
weighted_recall
1 [1,1]
weighted_recall
1 [1,1]
weighted_recall
1 [1,1]
weighted_recall
1 [1,1]
weighted_recall
1 [1,1]
weighted_recall
0.9845360824742269 [0.984252,0.985075]
weighted_recall
0.979381443298969 [0.976378,0.985075]
weighted_recall
0.9896907216494846 [0.984252,1]
weighted_recall
1 [1,1]
weighted_recall
0.9896907216494846 [0.992063,0.985294]