10576217
28997
Marc Boel
16
Supervised Classification
19037
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(1)
8292499
Python_3.8.10. Sklearn_0.24.2. NumPy_1.17.4. SciPy_1.3.3.
add_indicator
false
18819
copy
true
18819
fill_value
null
18819
missing_values
NaN
18819
strategy
"median"
18819
verbose
0
18819
n_jobs
null
18996
remainder
"drop"
18996
sparse_threshold
0.3
18996
transformer_weights
null
18996
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"}}}]
18996
verbose
false
18996
categories
"auto"
18997
drop
null
18997
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
18997
handle_unknown
"ignore"
18997
sparse
true
18997
memory
null
19037
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"}}]
19037
verbose
false
19037
ccp_alpha
0.0
19038
criterion
"friedman_mse"
19038
init
null
19038
learning_rate
0.848392724911614
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
19
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
190
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
7
19038
random_state
52664
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.2611548407814239
19038
verbose
0
19038
warm_start
false
19038
openml-python
Sklearn_0.24.2.
16
mfeat-karhunen
https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff
-1
22078701
description
https://api.openml.org/data/download/22078701/description.xml
-1
22078702
predictions
https://api.openml.org/data/download/22078702/predictions.arff
area_under_roc_curve
0.9966533333333334 [0.999125,0.997689,0.999739,0.99465,0.998514,0.991653,0.996956,0.998231,0.995494,0.994483]
average_cost
0
f_measure
0.9435779275441752 [0.964646,0.933985,0.97,0.931034,0.940299,0.916877,0.937824,0.965,0.921569,0.954545]
kappa
0.9372222222222222
kb_relative_information_score
0.9399017343306889
mean_absolute_error
0.014258711199811383
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.9435 [0.955,0.955,0.97,0.945,0.945,0.91,0.905,0.965,0.94,0.945]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9441592702238332 [0.97449,0.913876,0.97,0.917476,0.935644,0.923858,0.973118,0.965,0.903846,0.964286]
predictive_accuracy
0.9434999999999999
prior_entropy
3.3219280948872383
relative_absolute_error
0.0792150622211719
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.09468556110724487
root_relative_squared_error
0.3156185370241447
total_cost
0
unweighted_recall
0.9435 [0.955,0.955,0.97,0.945,0.945,0.91,0.905,0.965,0.94,0.945]
area_under_roc_curve
0.9958611111111111 [0.995833,0.993889,1,0.998889,1,0.981667,0.998611,1,0.990556,0.999167]
area_under_roc_curve
0.9964444444444445 [0.999722,0.995,0.999444,0.991389,0.996667,0.99,0.999444,0.995556,0.998889,0.998333]
area_under_roc_curve
0.997777777777778 [0.998611,0.999167,1,0.996111,0.998611,0.993333,0.998889,0.997222,0.996944,0.998889]
area_under_roc_curve
0.9972222222222222 [0.999722,1,0.999444,0.984167,0.9975,0.997222,1,1,0.998333,0.995833]
area_under_roc_curve
0.9949166666666669 [0.999722,0.998889,0.997778,0.989444,0.999444,0.970833,1,0.996667,0.9975,0.998889]
area_under_roc_curve
0.997138888888889 [1,0.998889,1,1,0.998333,0.992222,0.997222,1,0.998611,0.986111]
area_under_roc_curve
0.998 [1,0.996389,1,1,0.998889,0.9975,1,0.999444,0.995,0.992778]
area_under_roc_curve
0.9979444444444445 [1,0.997778,1,0.9975,0.999444,0.995833,0.997222,0.999722,0.991944,1]
area_under_roc_curve
0.9985277777777776 [1,0.999722,1,0.990833,1,0.997222,1,1,0.997778,0.999722]
area_under_roc_curve
0.9942222222222223 [1,0.998611,1,0.9975,0.998611,0.996944,0.983056,0.989722,0.992222,0.985556]
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
0.9354490544831471 [0.923077,0.894737,1,0.904762,0.97561,0.974359,0.894737,1,0.837209,0.95]
f_measure
0.9297689110205155 [0.952381,0.926829,0.923077,0.923077,0.894737,0.904762,0.947368,0.923077,0.952381,0.95]
f_measure
0.9452125858736897 [0.947368,0.95,0.974359,0.974359,0.926829,0.9,0.926829,0.95,0.95,0.952381]
f_measure
0.9651094434021261 [0.95,0.97561,0.97561,0.926829,0.974359,0.974359,0.974359,0.97561,0.95,0.974359]
f_measure
0.9352036517184142 [0.95,0.926829,0.9,0.923077,0.947368,0.9,1,0.95,0.904762,0.95]
f_measure
0.9337456250765431 [1,0.952381,0.97561,0.974359,0.926829,0.878049,0.823529,0.97561,0.883721,0.947368]
f_measure
0.9549472414620038 [0.947368,0.952381,1,0.952381,0.95,0.923077,1,0.974359,0.926829,0.923077]
f_measure
0.9499711330199134 [1,0.904762,0.974359,0.904762,0.952381,0.918919,0.95,0.97561,0.918919,1]
f_measure
0.9501396161331378 [0.974359,0.95,0.97561,0.904762,0.930233,0.894737,0.947368,0.97561,0.974359,0.974359]
f_measure
0.9351441455420916 [1,0.904762,1,0.926829,0.923077,0.904762,0.894737,0.947368,0.926829,0.923077]
kappa
0.9277777777777778
kappa
0.9222222222222223
kappa
0.9388888888888889
kappa
0.961111111111111
kappa
0.9277777777777778
kappa
0.9277777777777778
kappa
0.95
kappa
0.9444444444444444
kappa
0.9444444444444444
kappa
0.9277777777777778
kb_relative_information_score
0.9396454996185208
kb_relative_information_score
0.9253186201243541
kb_relative_information_score
0.9325891350342437
kb_relative_information_score
0.9584987523908082
kb_relative_information_score
0.9290070261235389
kb_relative_information_score
0.935805276306595
kb_relative_information_score
0.9469441749833801
kb_relative_information_score
0.9442716613401785
kb_relative_information_score
0.9547929129686505
kb_relative_information_score
0.9321442844162892
mean_absolute_error
0.013807684703759437
mean_absolute_error
0.017100307240936037
mean_absolute_error
0.016445408429730003
mean_absolute_error
0.01069126129917437
mean_absolute_error
0.017972168339407003
mean_absolute_error
0.013080417171405692
mean_absolute_error
0.013345037672135978
mean_absolute_error
0.01350364731838427
mean_absolute_error
0.01044434178408007
mean_absolute_error
0.016196838039100672
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
mean_prior_absolute_error
0.1799999999999998
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
number_of_instances
200 [20,20,20,20,20,20,20,20,20,20]
precision
0.9384883321611011 [0.947368,0.944444,1,0.863636,0.952381,1,0.944444,1,0.782609,0.95]
precision
0.9323129794182425 [0.909091,0.904762,0.947368,0.947368,0.944444,0.863636,1,0.947368,0.909091,0.95]
precision
0.946861471861472 [1,0.95,1,1,0.904762,0.9,0.904762,0.95,0.95,0.909091]
precision
0.9661904761904762 [0.95,0.952381,0.952381,0.904762,1,1,1,0.952381,0.95,1]
precision
0.9365766689450901 [0.95,0.904762,0.9,0.947368,1,0.9,1,0.95,0.863636,0.95]
precision
0.9401844532279314 [1,0.909091,0.952381,1,0.904762,0.857143,1,0.952381,0.826087,1]
precision
0.9567680565048985 [1,0.909091,1,0.909091,0.95,0.947368,1,1,0.904762,0.947368]
precision
0.9538744588744588 [1,0.863636,1,0.863636,0.909091,1,0.95,0.952381,1,1]
precision
0.9532407930234017 [1,0.95,0.952381,0.863636,0.869565,0.944444,1,0.952381,1,1]
precision
0.9375977823346244 [1,0.863636,1,0.904762,0.947368,0.863636,0.944444,1,0.904762,0.947368]
predictive_accuracy
0.935
predictive_accuracy
0.93
predictive_accuracy
0.945
predictive_accuracy
0.965
predictive_accuracy
0.935
predictive_accuracy
0.935
predictive_accuracy
0.955
predictive_accuracy
0.95
predictive_accuracy
0.95
predictive_accuracy
0.935
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
prior_entropy
3.321928094887355
relative_absolute_error
0.07670935946533029
relative_absolute_error
0.0950017068940892
relative_absolute_error
0.0913633801651668
relative_absolute_error
0.05939589610652435
relative_absolute_error
0.09984537966337234
relative_absolute_error
0.07266898428558725
relative_absolute_error
0.0741390981785333
relative_absolute_error
0.07502026287991269
relative_absolute_error
0.058024121022667116
relative_absolute_error
0.08998243355055939
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_prior_squared_error
0.2999999999999998
root_mean_squared_error
0.09633051947983408
root_mean_squared_error
0.10520244992906232
root_mean_squared_error
0.09895602256016853
root_mean_squared_error
0.07520100711747815
root_mean_squared_error
0.09882022473445842
root_mean_squared_error
0.10170171797174117
root_mean_squared_error
0.08788485946998709
root_mean_squared_error
0.0912180328931801
root_mean_squared_error
0.08369522335975578
root_mean_squared_error
0.10344515347768822
root_relative_squared_error
0.3211017315994471
root_relative_squared_error
0.3506748330968746
root_relative_squared_error
0.32985340853389533
root_relative_squared_error
0.25067002372492736
root_relative_squared_error
0.32940074911486156
root_relative_squared_error
0.33900572657247074
root_relative_squared_error
0.2929495315666238
root_relative_squared_error
0.3040601096439339
root_relative_squared_error
0.2789840778658528
root_relative_squared_error
0.3448171782589609
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
0.9349999999999999 [0.9,0.85,1,0.95,1,0.95,0.85,1,0.9,0.95]
unweighted_recall
0.93 [1,0.95,0.9,0.9,0.85,0.95,0.9,0.9,1,0.95]
unweighted_recall
0.9450000000000001 [0.9,0.95,0.95,0.95,0.95,0.9,0.95,0.95,0.95,1]
unweighted_recall
0.9650000000000001 [0.95,1,1,0.95,0.95,0.95,0.95,1,0.95,0.95]
unweighted_recall
0.9349999999999999 [0.95,0.95,0.9,0.9,0.9,0.9,1,0.95,0.95,0.95]
unweighted_recall
0.9350000000000002 [1,1,1,0.95,0.95,0.9,0.7,1,0.95,0.9]
unweighted_recall
0.9550000000000001 [0.9,1,1,1,0.95,0.9,1,0.95,0.95,0.9]
unweighted_recall
0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1]
unweighted_recall
0.9499999999999998 [0.95,0.95,1,0.95,1,0.85,0.9,1,0.95,0.95]
unweighted_recall
0.9350000000000002 [1,0.95,1,0.95,0.9,0.95,0.85,0.9,0.95,0.9]
usercpu_time_millis
3923.059149000437
usercpu_time_millis
2971.0428359994694
usercpu_time_millis
3657.2285479996935
usercpu_time_millis
3502.716042999964
usercpu_time_millis
2986.3245370006553
usercpu_time_millis
5075.0812599999335
usercpu_time_millis
3522.3215409996556
usercpu_time_millis
3806.5721459997803
usercpu_time_millis
4152.544149999812
usercpu_time_millis
3295.081941000717
usercpu_time_millis_testing
2.6119989997823723
usercpu_time_millis_testing
2.6170000001002336
usercpu_time_millis_testing
3.2712999991417746
usercpu_time_millis_testing
2.690999999686028
usercpu_time_millis_testing
3.344200000356068
usercpu_time_millis_testing
2.864899999622139
usercpu_time_millis_testing
3.6145999993095757
usercpu_time_millis_testing
2.5848999994195765
usercpu_time_millis_testing
2.7046000004702364
usercpu_time_millis_testing
3.3196000003954396
usercpu_time_millis_training
3920.447150000655
usercpu_time_millis_training
2968.425835999369
usercpu_time_millis_training
3653.9572480005518
usercpu_time_millis_training
3500.025043000278
usercpu_time_millis_training
2982.980337000299
usercpu_time_millis_training
5072.216360000311
usercpu_time_millis_training
3518.706941000346
usercpu_time_millis_training
3803.9872460003608
usercpu_time_millis_training
4149.839549999342
usercpu_time_millis_training
3291.7623410003216
wall_clock_time_millis
3925.997734069824
wall_clock_time_millis
2972.522258758545
wall_clock_time_millis
3659.5664024353027
wall_clock_time_millis
3502.781391143799
wall_clock_time_millis
2989.5639419555664
wall_clock_time_millis
5093.977928161621
wall_clock_time_millis
3525.908946990967
wall_clock_time_millis
3811.248540878296
wall_clock_time_millis
4157.371759414673
wall_clock_time_millis
3300.093412399292
wall_clock_time_millis_testing
2.6094913482666016
wall_clock_time_millis_testing
2.6204586029052734
wall_clock_time_millis_testing
3.273487091064453
wall_clock_time_millis_testing
2.694368362426758
wall_clock_time_millis_testing
3.3490657806396484
wall_clock_time_millis_testing
2.867460250854492
wall_clock_time_millis_testing
3.618001937866211
wall_clock_time_millis_testing
2.588987350463867
wall_clock_time_millis_testing
2.707242965698242
wall_clock_time_millis_testing
3.3228397369384766
wall_clock_time_millis_training
3923.3882427215576
wall_clock_time_millis_training
2969.9018001556396
wall_clock_time_millis_training
3656.2929153442383
wall_clock_time_millis_training
3500.087022781372
wall_clock_time_millis_training
2986.2148761749268
wall_clock_time_millis_training
5091.110467910767
wall_clock_time_millis_training
3522.2909450531006
wall_clock_time_millis_training
3808.659553527832
wall_clock_time_millis_training
4154.664516448975
wall_clock_time_millis_training
3296.7705726623535
weighted_recall
0.935 [0.9,0.85,1,0.95,1,0.95,0.85,1,0.9,0.95]
weighted_recall
0.93 [1,0.95,0.9,0.9,0.85,0.95,0.9,0.9,1,0.95]
weighted_recall
0.945 [0.9,0.95,0.95,0.95,0.95,0.9,0.95,0.95,0.95,1]
weighted_recall
0.965 [0.95,1,1,0.95,0.95,0.95,0.95,1,0.95,0.95]
weighted_recall
0.935 [0.95,0.95,0.9,0.9,0.9,0.9,1,0.95,0.95,0.95]
weighted_recall
0.935 [1,1,1,0.95,0.95,0.9,0.7,1,0.95,0.9]
weighted_recall
0.955 [0.9,1,1,1,0.95,0.9,1,0.95,0.95,0.9]
weighted_recall
0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1]
weighted_recall
0.95 [0.95,0.95,1,0.95,1,0.85,0.9,1,0.95,0.95]
weighted_recall
0.935 [1,0.95,1,0.95,0.9,0.95,0.85,0.9,0.95,0.9]