10576201
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)
8292483
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
0.8242446628205421
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
748
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
173
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
19
19038
random_state
62813
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.025996571702342
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
22078669
description
https://api.openml.org/data/download/22078669/description.xml
-1
22078670
predictions
https://api.openml.org/data/download/22078670/predictions.arff
area_under_roc_curve
0.9979025 [0.998853,0.998056,0.999819,0.996761,0.998475,0.995744,0.998258,0.997411,0.997989,0.997658]
average_cost
0
f_measure
0.9585133688574824 [0.972431,0.945813,0.98,0.940299,0.97,0.931646,0.969697,0.97,0.955,0.950249]
kappa
0.9538888888888889
kb_relative_information_score
0.9577516206515169
mean_absolute_error
0.008829021614701511
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.9585 [0.97,0.96,0.98,0.945,0.97,0.92,0.96,0.97,0.955,0.955]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9586282905947072 [0.974874,0.932039,0.98,0.935644,0.97,0.94359,0.979592,0.97,0.955,0.945545]
predictive_accuracy
0.9584999999999999
prior_entropy
3.3219280948872383
relative_absolute_error
0.04905012008167355
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.08568944100811521
root_relative_squared_error
0.2856314700270463
total_cost
0
unweighted_recall
0.9584999999999999 [0.97,0.96,0.98,0.945,0.97,0.92,0.96,0.97,0.955,0.955]
area_under_roc_curve
0.998388888888889 [0.998333,0.999167,1,1,1,0.9925,0.998889,1,0.995,1]
area_under_roc_curve
0.9987777777777778 [1,0.998056,1,0.995833,1,0.996111,0.999722,0.999167,1,0.998889]
area_under_roc_curve
0.99725 [0.999722,0.995833,1,1,1,0.996667,1,0.985833,0.999444,0.995]
area_under_roc_curve
0.9987777777777777 [1,0.999444,1,0.995278,0.997222,0.996944,1,1,0.999444,0.999444]
area_under_roc_curve
0.9980833333333333 [0.999722,1,0.999444,0.989444,1,0.993889,1,1,0.999444,0.998889]
area_under_roc_curve
0.9987222222222222 [1,0.999167,1,0.999722,0.998056,0.995,1,1,0.998333,0.996944]
area_under_roc_curve
0.9990000000000001 [0.9975,0.998889,0.999722,1,1,0.999167,1,1,0.998056,0.996667]
area_under_roc_curve
0.9988611111111112 [1,1,1,1,0.998611,0.996944,0.996944,1,0.996944,0.999167]
area_under_roc_curve
0.9989444444444444 [0.999444,1,0.999722,0.993333,0.999444,0.998333,0.999167,1,1,1]
area_under_roc_curve
0.9975277777777779 [0.999722,0.999444,1,0.999444,0.994444,0.999722,0.986667,0.999167,0.9975,0.999167]
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
0.9699785580273386 [0.974359,0.923077,1,1,0.97561,0.95,0.974359,1,0.95,0.952381]
f_measure
0.9549812382739212 [1,0.95,1,0.871795,0.974359,0.878049,0.97561,0.95,1,0.95]
f_measure
0.9600386601785235 [0.95,0.947368,0.97561,0.947368,1,0.926829,1,0.947368,0.97561,0.930233]
f_measure
0.9653246942129527 [0.974359,0.930233,0.97561,0.974359,0.974359,0.95,0.97561,0.974359,0.95,0.974359]
f_measure
0.9500762395499236 [0.952381,0.909091,0.947368,0.894737,0.947368,0.923077,1,1,0.974359,0.952381]
f_measure
0.9550364736615744 [0.97561,0.97561,0.974359,0.974359,0.95,0.923077,0.947368,0.930233,0.952381,0.947368]
f_measure
0.9598097870049089 [0.974359,0.95,0.95,1,0.97561,0.95,1,0.952381,0.926829,0.918919]
f_measure
0.9594449307016103 [0.97561,0.952381,1,0.930233,0.97561,0.947368,0.974359,1,0.888889,0.95]
f_measure
0.9652754207609866 [0.974359,0.974359,0.97561,0.883721,0.97561,0.894737,0.974359,1,1,1]
f_measure
0.9451772336290353 [0.974359,0.95,1,0.930233,0.95,0.974359,0.871795,0.947368,0.926829,0.926829]
kappa
0.9666666666666667
kappa
0.95
kappa
0.9555555555555555
kappa
0.961111111111111
kappa
0.9444444444444444
kappa
0.95
kappa
0.9555555555555555
kappa
0.9555555555555555
kappa
0.961111111111111
kappa
0.9388888888888889
kb_relative_information_score
0.965545993465831
kb_relative_information_score
0.9535542393140715
kb_relative_information_score
0.9621662891544469
kb_relative_information_score
0.9667501590304337
kb_relative_information_score
0.9515072273206665
kb_relative_information_score
0.9499821356564065
kb_relative_information_score
0.957064289635003
kb_relative_information_score
0.9644951224550637
kb_relative_information_score
0.9628041668297554
kb_relative_information_score
0.9436465836531324
mean_absolute_error
0.007117084850981916
mean_absolute_error
0.009510297302295788
mean_absolute_error
0.007791193099913147
mean_absolute_error
0.006888809315453749
mean_absolute_error
0.010215022115501652
mean_absolute_error
0.010276619893616022
mean_absolute_error
0.008405119153684195
mean_absolute_error
0.007874674008648686
mean_absolute_error
0.008462356392955455
mean_absolute_error
0.011749040013964348
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
0.9708840282524495 [1,0.947368,1,1,0.952381,0.95,1,1,0.95,0.909091]
precision
0.9554260651629072 [1,0.95,1,0.894737,1,0.857143,0.952381,0.95,1,0.95]
precision
0.9629089026915113 [0.95,1,0.952381,1,1,0.904762,1,1,0.952381,0.869565]
precision
0.9674327122153208 [1,0.869565,0.952381,1,1,0.95,0.952381,1,0.95,1]
precision
0.9543328017012227 [0.909091,0.833333,1,0.944444,1,0.947368,1,1,1,0.909091]
precision
0.958078645229675 [0.952381,0.952381,1,1,0.95,0.947368,1,0.869565,0.909091,1]
precision
0.9616233766233766 [1,0.95,0.95,1,0.952381,0.95,1,0.909091,0.904762,1]
precision
0.9633418031244119 [0.952381,0.909091,1,0.869565,0.952381,1,1,1,1,0.95]
precision
0.9675293305728089 [1,1,0.952381,0.826087,0.952381,0.944444,1,1,1,1]
precision
0.9473825869020378 [1,0.95,1,0.869565,0.95,1,0.894737,1,0.904762,0.904762]
predictive_accuracy
0.97
predictive_accuracy
0.955
predictive_accuracy
0.96
predictive_accuracy
0.965
predictive_accuracy
0.95
predictive_accuracy
0.955
predictive_accuracy
0.96
predictive_accuracy
0.96
predictive_accuracy
0.965
predictive_accuracy
0.945
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
0.03953936028323291
relative_absolute_error
0.05283498501275444
relative_absolute_error
0.04328440611062865
relative_absolute_error
0.03827116286363198
relative_absolute_error
0.05675012286389814
relative_absolute_error
0.0570923327423113
relative_absolute_error
0.04669510640935669
relative_absolute_error
0.043748188936937195
relative_absolute_error
0.0470130910719748
relative_absolute_error
0.06527244452202423
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
0.07542005963601604
root_mean_squared_error
0.09026930785305068
root_mean_squared_error
0.08295725556227827
root_mean_squared_error
0.0722599695440402
root_mean_squared_error
0.09320622540983207
root_mean_squared_error
0.0950354553907492
root_mean_squared_error
0.08774011757086932
root_mean_squared_error
0.07517969066098233
root_mean_squared_error
0.07963797690090105
root_mean_squared_error
0.10037430197793584
root_relative_squared_error
0.25140019878672026
root_relative_squared_error
0.30089769284350243
root_relative_squared_error
0.2765241852075944
root_relative_squared_error
0.2408665651468008
root_relative_squared_error
0.3106874180327738
root_relative_squared_error
0.31678485130249756
root_relative_squared_error
0.29246705856956456
root_relative_squared_error
0.25059896886994126
root_relative_squared_error
0.26545992300300364
root_relative_squared_error
0.3345810065931197
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
0.97 [0.95,0.9,1,1,1,0.95,0.95,1,0.95,1]
unweighted_recall
0.9550000000000001 [1,0.95,1,0.85,0.95,0.9,1,0.95,1,0.95]
unweighted_recall
0.9600000000000002 [0.95,0.9,1,0.9,1,0.95,1,0.9,1,1]
unweighted_recall
0.9650000000000001 [0.95,1,1,0.95,0.95,0.95,1,0.95,0.95,0.95]
unweighted_recall
0.95 [1,1,0.9,0.85,0.9,0.9,1,1,0.95,1]
unweighted_recall
0.9550000000000003 [1,1,0.95,0.95,0.95,0.9,0.9,1,1,0.9]
unweighted_recall
0.96 [0.95,0.95,0.95,1,1,0.95,1,1,0.95,0.85]
unweighted_recall
0.96 [1,1,1,1,1,0.9,0.95,1,0.8,0.95]
unweighted_recall
0.9649999999999999 [0.95,0.95,1,0.95,1,0.85,0.95,1,1,1]
unweighted_recall
0.945 [0.95,0.95,1,1,0.95,0.95,0.85,0.9,0.95,0.95]
usercpu_time_millis
20629.80985700051
usercpu_time_millis
20706.653059000928
usercpu_time_millis
17284.650915000384
usercpu_time_millis
16521.20840599946
usercpu_time_millis
16807.939309000176
usercpu_time_millis
17767.583215999366
usercpu_time_millis
16551.55849499988
usercpu_time_millis
11018.453038999724
usercpu_time_millis
8236.174804000257
usercpu_time_millis
13314.163662999817
usercpu_time_millis_testing
4.250799999681476
usercpu_time_millis_testing
4.334400000516325
usercpu_time_millis_testing
3.8561000001209322
usercpu_time_millis_testing
4.440800999873318
usercpu_time_millis_testing
3.958700000112003
usercpu_time_millis_testing
4.265399999894726
usercpu_time_millis_testing
4.039800000100513
usercpu_time_millis_testing
3.9465010004278156
usercpu_time_millis_testing
3.645001000222692
usercpu_time_millis_testing
3.4967999999935273
usercpu_time_millis_training
20625.559057000828
usercpu_time_millis_training
20702.31865900041
usercpu_time_millis_training
17280.794815000263
usercpu_time_millis_training
16516.767604999586
usercpu_time_millis_training
16803.980609000064
usercpu_time_millis_training
17763.31781599947
usercpu_time_millis_training
16547.51869499978
usercpu_time_millis_training
11014.506537999296
usercpu_time_millis_training
8232.529803000034
usercpu_time_millis_training
13310.666862999824
wall_clock_time_millis
20645.529985427856
wall_clock_time_millis
20727.927446365356
wall_clock_time_millis
17297.741651535034
wall_clock_time_millis
16528.145790100098
wall_clock_time_millis
16814.929485321045
wall_clock_time_millis
17771.379470825195
wall_clock_time_millis
16601.584672927856
wall_clock_time_millis
11047.981977462769
wall_clock_time_millis
8239.75133895874
wall_clock_time_millis
13327.873706817627
wall_clock_time_millis_testing
4.253864288330078
wall_clock_time_millis_testing
4.337072372436523
wall_clock_time_millis_testing
3.8597583770751953
wall_clock_time_millis_testing
4.446744918823242
wall_clock_time_millis_testing
3.9620399475097656
wall_clock_time_millis_testing
4.268884658813477
wall_clock_time_millis_testing
4.043817520141602
wall_clock_time_millis_testing
3.9505958557128906
wall_clock_time_millis_testing
3.6492347717285156
wall_clock_time_millis_testing
3.503561019897461
wall_clock_time_millis_training
20641.276121139526
wall_clock_time_millis_training
20723.59037399292
wall_clock_time_millis_training
17293.88189315796
wall_clock_time_millis_training
16523.699045181274
wall_clock_time_millis_training
16810.967445373535
wall_clock_time_millis_training
17767.110586166382
wall_clock_time_millis_training
16597.540855407715
wall_clock_time_millis_training
11044.031381607056
wall_clock_time_millis_training
8236.102104187012
wall_clock_time_millis_training
13324.37014579773
weighted_recall
0.97 [0.95,0.9,1,1,1,0.95,0.95,1,0.95,1]
weighted_recall
0.955 [1,0.95,1,0.85,0.95,0.9,1,0.95,1,0.95]
weighted_recall
0.96 [0.95,0.9,1,0.9,1,0.95,1,0.9,1,1]
weighted_recall
0.965 [0.95,1,1,0.95,0.95,0.95,1,0.95,0.95,0.95]
weighted_recall
0.95 [1,1,0.9,0.85,0.9,0.9,1,1,0.95,1]
weighted_recall
0.955 [1,1,0.95,0.95,0.95,0.9,0.9,1,1,0.9]
weighted_recall
0.96 [0.95,0.95,0.95,1,1,0.95,1,1,0.95,0.85]
weighted_recall
0.96 [1,1,1,1,1,0.9,0.95,1,0.8,0.95]
weighted_recall
0.965 [0.95,0.95,1,0.95,1,0.85,0.95,1,1,1]
weighted_recall
0.945 [0.95,0.95,1,1,0.95,0.95,0.85,0.9,0.95,0.95]