10218703
1
Jan van Rijn
3494
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)
8144135
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": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3, 4, 5]}}]
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
0.0006357157695232822
9667
loss
"deviance"
9667
max_depth
3
9667
max_features
0.8996129746250127
9667
max_leaf_nodes
null
9667
min_impurity_decrease
0.6728327267849243
9667
min_impurity_split
null
9667
min_samples_leaf
18
9667
min_samples_split
10
9667
min_weight_fraction_leaf
0.08859115990192873
9667
n_estimators
1152
9667
n_iter_no_change
1734
9667
presort
"auto"
9667
random_state
28507
9667
subsample
0.7391341058428973
9667
tol
9.462018835380364e-05
9667
validation_fraction
0.11977705666514249
9667
verbose
0
9667
warm_start
false
9667
openml-python
Sklearn_0.20.3.
335
monks-problems-3
https://www.openml.org/data/download/52238/phphZierv
-1
21358322
description
https://api.openml.org/data/download/21358322/description.xml
-1
21358323
predictions
https://api.openml.org/data/download/21358323/predictions.arff
area_under_roc_curve
0.9853866436925648 [0.985387,0.985387]
average_cost
0
f_measure
0.9639130386277776 [0.9631,0.964664]
kappa
0.9277874814254804
kb_relative_information_score
296.6178548519409
mean_absolute_error
0.2713594937023081
mean_prior_absolute_error
0.4992143469340059
number_of_instances
554 [266,288]
precision
0.9645552746313386 [0.945652,0.982014]
predictive_accuracy
0.9638989169675091
prior_entropy
0.9988703245161819
recall
0.9638989169675091 [0.981203,0.947917]
relative_absolute_error
0.5435731071610823
root_mean_prior_squared_error
0.49960560487440536
root_mean_squared_error
0.28330122177861455
root_relative_squared_error
0.5670497268537108
total_cost
0
area_under_roc_curve
0.979565772669221 [0.979566,0.979566]
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
1 [1,1]
area_under_roc_curve
0.9907161803713528 [0.990716,0.990716]
area_under_roc_curve
0.9754641909814323 [0.975464,0.975464]
area_under_roc_curve
1 [1,1]
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
0.9642857142857143 [0.962963,0.965517]
f_measure
0.9821485532011848 [0.981818,0.982456]
f_measure
0.9642857142857143 [0.964286,0.964286]
f_measure
0.9642857142857143 [0.964286,0.964286]
f_measure
0.9818181818181818 [0.981818,0.981818]
f_measure
0.9636123136123137 [0.964286,0.962963]
f_measure
0.9636604136604137 [0.962963,0.964286]
f_measure
0.9453820357110487 [0.941176,0.949153]
f_measure
0.9091510938581445 [0.90566,0.912281]
f_measure
1 [1,1]
kappa
0.9284802043422733
kappa
0.9642857142857142
kappa
0.9286624203821655
kappa
0.9286624203821655
kappa
0.9636483807005949
kappa
0.927344782034346
kappa
0.927344782034346
kappa
0.8903654485049833
kappa
0.8180013236267372
kappa
1
kb_relative_information_score
30.475669259494957
kb_relative_information_score
30.66374846294996
kb_relative_information_score
30.498349466283607
kb_relative_information_score
30.322203637947425
kb_relative_information_score
30.832053657881403
kb_relative_information_score
29.370364227236706
kb_relative_information_score
29.331986729261402
kb_relative_information_score
28.60148234336759
kb_relative_information_score
26.028942971611315
kb_relative_information_score
30.493054095906768
mean_absolute_error
0.2669440120669787
mean_absolute_error
0.26695340201929124
mean_absolute_error
0.2671476712583837
mean_absolute_error
0.26870451269405365
mean_absolute_error
0.2609551849407833
mean_absolute_error
0.2727230234521702
mean_absolute_error
0.2720434286759578
mean_absolute_error
0.2769668966200138
mean_absolute_error
0.29726539100392513
mean_absolute_error
0.2641766575055311
mean_prior_absolute_error
0.4992934224049325
mean_prior_absolute_error
0.4992934224049325
mean_prior_absolute_error
0.4992934224049325
mean_prior_absolute_error
0.4992934224049325
mean_prior_absolute_error
0.4996402877697835
mean_prior_absolute_error
0.4996402877697835
mean_prior_absolute_error
0.49892086330935187
mean_prior_absolute_error
0.49892086330935187
mean_prior_absolute_error
0.49892086330935187
mean_prior_absolute_error
0.49892086330935187
number_of_instances
56 [27,29]
number_of_instances
56 [27,29]
number_of_instances
56 [27,29]
number_of_instances
56 [27,29]
number_of_instances
55 [27,28]
number_of_instances
55 [27,28]
number_of_instances
55 [26,29]
number_of_instances
55 [26,29]
number_of_instances
55 [26,29]
number_of_instances
55 [26,29]
precision
0.9642857142857143 [0.962963,0.965517]
precision
0.982780612244898 [0.964286,1]
precision
0.9667487684729065 [0.931034,1]
precision
0.9667487684729065 [0.931034,1]
precision
0.9824675324675325 [0.964286,1]
precision
0.9661442006269593 [0.931034,1]
precision
0.9662337662337661 [0.928571,1]
precision
0.945939393939394 [0.96,0.933333]
precision
0.90981240981241 [0.888889,0.928571]
precision
1 [1,1]
predictive_accuracy
0.9642857142857143
predictive_accuracy
0.9821428571428571
predictive_accuracy
0.9642857142857143
predictive_accuracy
0.9642857142857143
predictive_accuracy
0.9818181818181819
predictive_accuracy
0.9636363636363636
predictive_accuracy
0.9636363636363636
predictive_accuracy
0.9454545454545454
predictive_accuracy
0.9090909090909091
predictive_accuracy
1
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
prior_entropy
0.9988703245161819
recall
0.9642857142857143 [0.962963,0.965517]
recall
0.9821428571428571 [1,0.965517]
recall
0.9642857142857143 [1,0.931034]
recall
0.9642857142857143 [1,0.931034]
recall
0.9818181818181818 [1,0.964286]
recall
0.9636363636363636 [1,0.928571]
recall
0.9636363636363636 [1,0.931034]
recall
0.9454545454545454 [0.923077,0.965517]
recall
0.9090909090909091 [0.923077,0.896552]
recall
1 [1,1]
relative_absolute_error
0.5346435584534581
relative_absolute_error
0.5346623649345595
relative_absolute_error
0.5350514532549238
relative_absolute_error
0.5381695424702216
relative_absolute_error
0.5222861152882495
relative_absolute_error
0.5458387366429333
relative_absolute_error
0.5452636854500098
relative_absolute_error
0.5551319196853924
relative_absolute_error
0.5958167173690793
relative_absolute_error
0.529496112375903
root_mean_prior_squared_error
0.49968473650177464
root_mean_prior_squared_error
0.49968473650177464
root_mean_prior_squared_error
0.49968473650177464
root_mean_prior_squared_error
0.49968473650177464
root_mean_prior_squared_error
0.5000317002527929
root_mean_prior_squared_error
0.5000317002527929
root_mean_prior_squared_error
0.49931180318240753
root_mean_prior_squared_error
0.49931180318240753
root_mean_prior_squared_error
0.49931180318240753
root_mean_prior_squared_error
0.49931180318240753
root_mean_squared_error
0.2825856654061621
root_mean_squared_error
0.2722753673675748
root_mean_squared_error
0.27584779917281765
root_mean_squared_error
0.2776850623393433
root_mean_squared_error
0.2666543887749207
root_mean_squared_error
0.28283431812062293
root_mean_squared_error
0.2824050305799303
root_mean_squared_error
0.2975478880593648
root_mean_squared_error
0.3244903959130759
root_mean_squared_error
0.2664149097544448
root_relative_squared_error
0.5655279114277257
root_relative_squared_error
0.5448943053048566
root_relative_squared_error
0.5520436767870694
root_relative_squared_error
0.5557205214699551
root_relative_squared_error
0.5332749676472764
root_relative_squared_error
0.5656327748373453
root_relative_squared_error
0.5655885336176656
root_relative_squared_error
0.595915991095979
root_relative_squared_error
0.6498752760197294
root_relative_squared_error
0.5335642138968598
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
1003.9532490009151
usercpu_time_millis
941.3277690000541
usercpu_time_millis
941.7302879955969
usercpu_time_millis
935.2583479994792
usercpu_time_millis
930.7182809970982
usercpu_time_millis
933.2291189966782
usercpu_time_millis
925.9927699968102
usercpu_time_millis
928.9386050004396
usercpu_time_millis
923.1227269992814
usercpu_time_millis
941.1096570038353
usercpu_time_millis_testing
2.6190380012849346
usercpu_time_millis_testing
2.5929240000550635
usercpu_time_millis_testing
2.606099998956779
usercpu_time_millis_testing
2.62238499999512
usercpu_time_millis_testing
2.5660439969215076
usercpu_time_millis_testing
2.5113359988608863
usercpu_time_millis_testing
2.5425519997952506
usercpu_time_millis_testing
2.627718000439927
usercpu_time_millis_testing
2.6470339980733115
usercpu_time_millis_testing
2.6353620014560875
usercpu_time_millis_training
1001.3342109996302
usercpu_time_millis_training
938.734844999999
usercpu_time_millis_training
939.1241879966401
usercpu_time_millis_training
932.635962999484
usercpu_time_millis_training
928.1522370001767
usercpu_time_millis_training
930.7177829978173
usercpu_time_millis_training
923.450217997015
usercpu_time_millis_training
926.3108869999996
usercpu_time_millis_training
920.4756930012081
usercpu_time_millis_training
938.4742950023792