10576160
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)
8292442
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
0.689627483734651
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
67
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
167
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
16
19038
random_state
23456
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.3012135283152982
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
22078587
description
https://api.openml.org/data/download/22078587/description.xml
-1
22078588
predictions
https://api.openml.org/data/download/22078588/predictions.arff
area_under_roc_curve
0.99762 [0.999156,0.998247,0.999478,0.995608,0.998692,0.995319,0.998044,0.9992,0.997239,0.995217]
average_cost
0
f_measure
0.9484470367219074 [0.977667,0.944039,0.9801,0.927318,0.952618,0.917293,0.956298,0.962779,0.929648,0.936709]
kappa
0.9427777777777778
kb_relative_information_score
0.9483394051806523
mean_absolute_error
0.01165706097036198
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.9485 [0.985,0.97,0.985,0.925,0.955,0.915,0.93,0.97,0.925,0.925]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9487470533320616 [0.970443,0.919431,0.975248,0.929648,0.950249,0.919598,0.984127,0.955665,0.934343,0.948718]
predictive_accuracy
0.9484999999999999
prior_entropy
3.3219280948872383
relative_absolute_error
0.06476144983534234
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.0897439014094729
root_relative_squared_error
0.29914633803157176
total_cost
0
unweighted_recall
0.9485000000000001 [0.985,0.97,0.985,0.925,0.955,0.915,0.93,0.97,0.925,0.925]
area_under_roc_curve
0.9969166666666667 [0.997778,0.995556,1,1,1,0.988333,0.998611,1,0.989722,0.999167]
area_under_roc_curve
0.9971944444444446 [1,0.998056,1,0.984167,0.998333,0.995556,0.998333,0.999167,0.999167,0.999167]
area_under_roc_curve
0.9978888888888888 [1,0.996389,1,0.999722,1,0.988333,1,0.997778,1,0.996667]
area_under_roc_curve
0.9980833333333333 [1,1,1,0.990556,0.998056,0.996944,1,0.998889,1,0.996389]
area_under_roc_curve
0.9972500000000001 [0.999167,0.999444,0.994167,0.993056,0.9975,0.997222,1,0.998889,0.998056,0.995]
area_under_roc_curve
0.9978888888888889 [1,0.998889,1,1,0.996667,0.995556,0.996111,1,0.9975,0.994167]
area_under_roc_curve
0.9958333333333332 [0.996389,0.998889,0.999722,0.999722,0.999722,0.998333,1,1,0.996389,0.969167]
area_under_roc_curve
0.9989444444444444 [1,0.999444,1,0.999722,0.999167,0.998333,0.997222,1,0.995556,1]
area_under_roc_curve
0.9991111111111111 [1,1,1,0.993889,1,0.997778,1,1,1,0.999444]
area_under_roc_curve
0.9979444444444445 [1,0.999722,1,0.998056,1,0.996944,0.992222,0.998611,0.996667,0.997222]
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
0.9452036517184141 [0.95,0.926829,1,0.947368,1,0.95,0.923077,1,0.85,0.904762]
f_measure
0.9404457009312667 [1,0.883721,0.97561,0.894737,0.918919,0.857143,0.974359,0.97561,0.95,0.974359]
f_measure
0.9600478822430043 [1,0.974359,1,0.918919,0.97561,0.9,1,0.926829,1,0.904762]
f_measure
0.9650942553381577 [1,0.97561,0.952381,0.923077,0.974359,0.974359,0.97561,0.926829,0.974359,0.974359]
f_measure
0.9159258014797316 [0.930233,0.909091,0.947368,0.837209,0.918919,0.871795,0.947368,0.947368,0.926829,0.923077]
f_measure
0.9392146153121763 [1,0.952381,0.97561,1,0.9,0.9,0.864865,0.97561,0.904762,0.918919]
f_measure
0.9494549224844475 [0.974359,0.95,0.97561,0.95,0.97561,0.926829,1,0.97561,0.871795,0.894737]
f_measure
0.9498293887125722 [0.97561,0.95,0.974359,0.95,0.909091,0.894737,0.974359,0.97561,0.918919,0.97561]
f_measure
0.9652094589193433 [0.974359,0.974359,1,0.926829,0.952381,0.926829,0.974359,0.97561,1,0.947368]
f_measure
0.9548869580948574 [0.97561,0.952381,1,0.930233,1,0.974359,0.918919,0.947368,0.9,0.95]
kappa
0.9388888888888889
kappa
0.9333333333333332
kappa
0.9555555555555555
kappa
0.961111111111111
kappa
0.9055555555555556
kappa
0.9333333333333332
kappa
0.9444444444444444
kappa
0.9444444444444444
kappa
0.961111111111111
kappa
0.95
kb_relative_information_score
0.9499206876775537
kb_relative_information_score
0.9361682841136263
kb_relative_information_score
0.9570194982792934
kb_relative_information_score
0.9636390816248553
kb_relative_information_score
0.9197022723292136
kb_relative_information_score
0.9422096407465763
kb_relative_information_score
0.9471846967578043
kb_relative_information_score
0.9546426094822802
kb_relative_information_score
0.9649696434964179
kb_relative_information_score
0.9479376372985739
mean_absolute_error
0.011107059997218283
mean_absolute_error
0.013373029364674716
mean_absolute_error
0.010291491877343097
mean_absolute_error
0.008958607004099782
mean_absolute_error
0.017701193830327006
mean_absolute_error
0.012814439001804229
mean_absolute_error
0.012681486102168033
mean_absolute_error
0.011259392272025581
mean_absolute_error
0.007290412199382241
mean_absolute_error
0.011093498054576854
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
0.9465766689450901 [0.95,0.904762,1,1,1,0.95,0.947368,1,0.85,0.863636]
precision
0.9443475123909906 [1,0.826087,0.952381,0.944444,1,0.818182,1,0.952381,0.95,1]
precision
0.9620779220779221 [1,1,1,1,0.952381,0.9,1,0.904762,1,0.863636]
precision
0.966598313966735 [1,0.952381,0.909091,0.947368,1,1,0.952381,0.904762,1,1]
precision
0.9232374414296612 [0.869565,0.833333,1,0.782609,1,0.894737,1,1,0.904762,0.947368]
precision
0.9418665648077412 [1,0.909091,0.952381,1,0.9,0.9,0.941176,0.952381,0.863636,1]
precision
0.9501086048454469 [1,0.95,0.952381,0.95,0.952381,0.904762,1,0.952381,0.894737,0.944444]
precision
0.9534920634920634 [0.952381,0.95,1,0.95,0.833333,0.944444,1,0.952381,1,0.952381]
precision
0.9670995670995671 [1,1,1,0.904762,0.909091,0.904762,1,0.952381,1,1]
precision
0.9581037078863166 [0.952381,0.909091,1,0.869565,1,1,1,1,0.9,0.95]
predictive_accuracy
0.945
predictive_accuracy
0.94
predictive_accuracy
0.96
predictive_accuracy
0.965
predictive_accuracy
0.915
predictive_accuracy
0.94
predictive_accuracy
0.95
predictive_accuracy
0.95
predictive_accuracy
0.965
predictive_accuracy
0.955
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
0.06170588887343497
relative_absolute_error
0.07429460758152628
relative_absolute_error
0.05717495487412839
relative_absolute_error
0.04977003891166551
relative_absolute_error
0.09833996572403902
relative_absolute_error
0.07119132778780136
relative_absolute_error
0.07045270056760027
relative_absolute_error
0.06255217928903108
relative_absolute_error
0.04050228999656805
relative_absolute_error
0.06163054474764926
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
0.08953284334753919
root_mean_squared_error
0.10069755084068524
root_mean_squared_error
0.0847541347953808
root_mean_squared_error
0.07311856396331666
root_mean_squared_error
0.10872213924869555
root_mean_squared_error
0.09543571901587003
root_mean_squared_error
0.08938737305407624
root_mean_squared_error
0.0812504476502695
root_mean_squared_error
0.07463385977015895
root_mean_squared_error
0.09361374419280073
root_relative_squared_error
0.29844281115846416
root_relative_squared_error
0.3356585028022843
root_relative_squared_error
0.2825137826512695
root_relative_squared_error
0.243728546544389
root_relative_squared_error
0.36240713082898535
root_relative_squared_error
0.3181190633862336
root_relative_squared_error
0.2979579101802543
root_relative_squared_error
0.2708348255008985
root_relative_squared_error
0.24877953256719665
root_relative_squared_error
0.3120458139760027
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
0.945 [0.95,0.95,1,0.9,1,0.95,0.9,1,0.85,0.95]
unweighted_recall
0.9400000000000001 [1,0.95,1,0.85,0.85,0.9,0.95,1,0.95,0.95]
unweighted_recall
0.9600000000000002 [1,0.95,1,0.85,1,0.9,1,0.95,1,0.95]
unweighted_recall
0.9649999999999999 [1,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95]
unweighted_recall
0.915 [1,1,0.9,0.9,0.85,0.85,0.9,0.9,0.95,0.9]
unweighted_recall
0.9400000000000001 [1,1,1,1,0.9,0.9,0.8,1,0.95,0.85]
unweighted_recall
0.95 [0.95,0.95,1,0.95,1,0.95,1,1,0.85,0.85]
unweighted_recall
0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1]
unweighted_recall
0.9650000000000001 [0.95,0.95,1,0.95,1,0.95,0.95,1,1,0.9]
unweighted_recall
0.9549999999999998 [1,1,1,1,1,0.95,0.85,0.9,0.9,0.95]
usercpu_time_millis
5991.898573000071
usercpu_time_millis
5103.287863999867
usercpu_time_millis
5824.503370999992
usercpu_time_millis
4821.086359998844
usercpu_time_millis
4599.723454999548
usercpu_time_millis
5873.630370000683
usercpu_time_millis
4462.809357999504
usercpu_time_millis
5271.3460639988625
usercpu_time_millis
6709.08728500126
usercpu_time_millis
5700.307869000426
usercpu_time_millis_testing
3.109700000095472
usercpu_time_millis_testing
2.901199000007182
usercpu_time_millis_testing
2.986800000144285
usercpu_time_millis_testing
3.463999999439693
usercpu_time_millis_testing
3.4623999999894295
usercpu_time_millis_testing
2.954900000077032
usercpu_time_millis_testing
3.551099999640428
usercpu_time_millis_testing
2.8347999996185536
usercpu_time_millis_testing
3.2204000008277944
usercpu_time_millis_testing
3.034299999853829
usercpu_time_millis_training
5988.788872999976
usercpu_time_millis_training
5100.38666499986
usercpu_time_millis_training
5821.516570999847
usercpu_time_millis_training
4817.622359999405
usercpu_time_millis_training
4596.261054999559
usercpu_time_millis_training
5870.675470000606
usercpu_time_millis_training
4459.258257999863
usercpu_time_millis_training
5268.511263999244
usercpu_time_millis_training
6705.866885000432
usercpu_time_millis_training
5697.273569000572
wall_clock_time_millis
5996.711254119873
wall_clock_time_millis
5123.383045196533
wall_clock_time_millis
5829.820394515991
wall_clock_time_millis
4822.9053020477295
wall_clock_time_millis
4602.319240570068
wall_clock_time_millis
5885.390996932983
wall_clock_time_millis
4471.618413925171
wall_clock_time_millis
5290.244102478027
wall_clock_time_millis
6723.923921585083
wall_clock_time_millis
5705.971479415894
wall_clock_time_millis_testing
3.1137466430664062
wall_clock_time_millis_testing
2.904176712036133
wall_clock_time_millis_testing
2.9904842376708984
wall_clock_time_millis_testing
3.467559814453125
wall_clock_time_millis_testing
3.4673213958740234
wall_clock_time_millis_testing
2.9582977294921875
wall_clock_time_millis_testing
3.5560131072998047
wall_clock_time_millis_testing
2.838611602783203
wall_clock_time_millis_testing
3.223896026611328
wall_clock_time_millis_testing
3.0379295349121094
wall_clock_time_millis_training
5993.597507476807
wall_clock_time_millis_training
5120.478868484497
wall_clock_time_millis_training
5826.82991027832
wall_clock_time_millis_training
4819.437742233276
wall_clock_time_millis_training
4598.851919174194
wall_clock_time_millis_training
5882.432699203491
wall_clock_time_millis_training
4468.062400817871
wall_clock_time_millis_training
5287.405490875244
wall_clock_time_millis_training
6720.700025558472
wall_clock_time_millis_training
5702.933549880981
weighted_recall
0.945 [0.95,0.95,1,0.9,1,0.95,0.9,1,0.85,0.95]
weighted_recall
0.94 [1,0.95,1,0.85,0.85,0.9,0.95,1,0.95,0.95]
weighted_recall
0.96 [1,0.95,1,0.85,1,0.9,1,0.95,1,0.95]
weighted_recall
0.965 [1,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95]
weighted_recall
0.915 [1,1,0.9,0.9,0.85,0.85,0.9,0.9,0.95,0.9]
weighted_recall
0.94 [1,1,1,1,0.9,0.9,0.8,1,0.95,0.85]
weighted_recall
0.95 [0.95,0.95,1,0.95,1,0.95,1,1,0.85,0.85]
weighted_recall
0.95 [1,0.95,0.95,0.95,1,0.85,0.95,1,0.85,1]
weighted_recall
0.965 [0.95,0.95,1,0.95,1,0.95,0.95,1,1,0.9]
weighted_recall
0.955 [1,1,1,1,1,0.95,0.85,0.9,0.9,0.95]