10576461
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)
8292743
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
"most_frequent"
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
0.670485691026719
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
117
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
11
19038
random_state
25836
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.1702918585002705
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
22079189
description
https://api.openml.org/data/download/22079189/description.xml
-1
22079190
predictions
https://api.openml.org/data/download/22079190/predictions.arff
area_under_roc_curve
0.9977658333333334 [0.999347,0.997453,0.999669,0.995939,0.996761,0.996314,0.996881,0.999236,0.998197,0.997861]
average_cost
0
f_measure
0.9520531510693372 [0.982544,0.923457,0.982278,0.935323,0.962779,0.912281,0.959184,0.967901,0.952141,0.942643]
kappa
0.9466666666666667
kb_relative_information_score
0.9492142408451437
mean_absolute_error
0.011242481745344179
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.952 [0.985,0.935,0.97,0.94,0.97,0.91,0.94,0.98,0.945,0.945]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9523050975618783 [0.9801,0.912195,0.994872,0.930693,0.955665,0.914573,0.979167,0.956098,0.959391,0.940299]
predictive_accuracy
0.9520000000000001
prior_entropy
3.3219280948872383
relative_absolute_error
0.06245823191857685
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.08933282377504116
root_relative_squared_error
0.29777607925013266
total_cost
0
unweighted_recall
0.9520000000000002 [0.985,0.935,0.97,0.94,0.97,0.91,0.94,0.98,0.945,0.945]
area_under_roc_curve
0.998 [0.9975,0.996389,1,0.999444,1,0.991111,0.999444,1,0.996111,1]
area_under_roc_curve
0.998638888888889 [1,0.996389,1,0.996111,1,0.996389,0.999167,0.998889,1,0.999444]
area_under_roc_curve
0.9987222222222223 [1,0.9975,1,0.998889,1,0.9975,1,0.995833,1,0.9975]
area_under_roc_curve
0.9983888888888889 [1,0.998056,1,0.991111,0.9975,0.999167,1,0.999722,1,0.998333]
area_under_roc_curve
0.9951111111111112 [1,0.993611,0.999444,0.987778,0.985833,0.989444,0.999444,0.999722,0.998889,0.996944]
area_under_roc_curve
0.9969166666666667 [1,0.998056,1,1,0.985556,0.995278,0.997222,1,0.9975,0.995556]
area_under_roc_curve
0.9989166666666667 [0.998056,0.998333,0.998056,0.999444,1,0.998333,1,1,0.998611,0.998333]
area_under_roc_curve
0.9986666666666667 [1,0.998611,0.999444,0.998889,0.999167,0.998333,0.998889,1,0.993333,1]
area_under_roc_curve
0.9985 [1,1,1,0.989722,1,0.996389,0.999167,1,1,0.999722]
area_under_roc_curve
0.9972222222222222 [1,0.998611,1,0.999722,1,0.999167,0.979722,0.999167,0.998333,0.9975]
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
0.9549521082255354 [0.974359,0.878049,1,0.974359,0.97561,0.926829,0.974359,0.97561,0.894737,0.97561]
f_measure
0.9551031894934334 [1,0.923077,1,0.923077,1,0.878049,0.95,0.926829,1,0.95]
f_measure
0.9602118175802388 [1,0.918919,1,0.947368,0.952381,0.9,1,0.974359,1,0.909091]
f_measure
0.9601875232170481 [0.974359,0.904762,0.97561,0.947368,0.974359,0.926829,1,0.97561,0.97561,0.947368]
f_measure
0.9202701641533476 [0.952381,0.857143,0.947368,0.85,0.947368,0.871795,0.926829,0.952381,0.974359,0.923077]
f_measure
0.9498004061418694 [0.97561,0.95,0.974359,1,0.926829,0.926829,0.918919,0.952381,0.95,0.923077]
f_measure
0.9550447552886577 [0.974359,0.95,0.974359,0.95,0.97561,0.926829,1,0.97561,0.904762,0.918919]
f_measure
0.954780478400504 [1,0.926829,0.947368,0.952381,0.952381,0.947368,0.974359,1,0.894737,0.952381]
f_measure
0.9698462855073895 [0.97561,1,1,0.926829,0.97561,0.923077,0.947368,1,0.974359,0.97561]
f_measure
0.9403331973344212 [1,0.930233,1,0.888889,0.947368,0.894737,0.894737,0.947368,0.95,0.95]
kappa
0.95
kappa
0.95
kappa
0.9555555555555555
kappa
0.9555555555555555
kappa
0.9111111111111112
kappa
0.9444444444444444
kappa
0.95
kappa
0.95
kappa
0.9666666666666667
kappa
0.9333333333333332
kb_relative_information_score
0.9466312206732167
kb_relative_information_score
0.949841951950108
kb_relative_information_score
0.9579117509031602
kb_relative_information_score
0.958301157358337
kb_relative_information_score
0.9188854768975737
kb_relative_information_score
0.9453699501016914
kb_relative_information_score
0.953043811168798
kb_relative_information_score
0.9499846826720253
kb_relative_information_score
0.9679778551816658
kb_relative_information_score
0.9441945515445264
mean_absolute_error
0.011907968670867224
mean_absolute_error
0.010320130373079628
mean_absolute_error
0.00960348470330515
mean_absolute_error
0.009145495966192766
mean_absolute_error
0.018565581418628976
mean_absolute_error
0.012395251349455925
mean_absolute_error
0.009886817258170913
mean_absolute_error
0.01139455414477229
mean_absolute_error
0.007165558255949416
mean_absolute_error
0.01203997531301993
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
0.9563492063492062 [1,0.857143,1,1,0.952381,0.904762,1,0.952381,0.944444,0.952381]
precision
0.9556641604010025 [1,0.947368,1,0.947368,1,0.857143,0.95,0.904762,1,0.95]
precision
0.9642424242424242 [1,1,1,1,0.909091,0.9,1,1,1,0.833333]
precision
0.9625541125541125 [1,0.863636,0.952381,1,1,0.904762,1,0.952381,0.952381,1]
precision
0.9233230804283435 [0.909091,0.818182,1,0.85,1,0.894737,0.904762,0.909091,1,0.947368]
precision
0.9518364092048303 [0.952381,0.95,1,1,0.904762,0.904762,1,0.909091,0.95,0.947368]
precision
0.9573160173160172 [1,0.95,1,0.95,0.952381,0.904762,1,0.952381,0.863636,1]
precision
0.9576479076479076 [1,0.904762,1,0.909091,0.909091,1,1,1,0.944444,0.909091]
precision
0.9709273182957392 [0.952381,1,1,0.904762,0.952381,0.947368,1,1,1,0.952381]
precision
0.9458454106280193 [1,0.869565,1,0.8,1,0.944444,0.944444,1,0.95,0.95]
predictive_accuracy
0.955
predictive_accuracy
0.955
predictive_accuracy
0.96
predictive_accuracy
0.96
predictive_accuracy
0.92
predictive_accuracy
0.95
predictive_accuracy
0.955
predictive_accuracy
0.955
predictive_accuracy
0.97
predictive_accuracy
0.94
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
0.06615538150481798
relative_absolute_error
0.05733405762822022
relative_absolute_error
0.05335269279613977
relative_absolute_error
0.0508083109232932
relative_absolute_error
0.10314211899238332
relative_absolute_error
0.06886250749697743
relative_absolute_error
0.054926762545394026
relative_absolute_error
0.06330307858206835
relative_absolute_error
0.0398086569774968
relative_absolute_error
0.06688875173899969
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
0.0891555138223396
root_mean_squared_error
0.08771149389357397
root_mean_squared_error
0.08161479870416413
root_mean_squared_error
0.08165880906069715
root_mean_squared_error
0.10876964812394263
root_mean_squared_error
0.09466641226960495
root_mean_squared_error
0.08484131437836336
root_mean_squared_error
0.08884118503044504
root_mean_squared_error
0.07336172117963836
root_mean_squared_error
0.09781141489120314
root_relative_squared_error
0.29718504607446555
root_relative_squared_error
0.2923716463119134
root_relative_squared_error
0.27204932901388057
root_relative_squared_error
0.27219603020232397
root_relative_squared_error
0.3625654937464756
root_relative_squared_error
0.31555470756535003
root_relative_squared_error
0.2828043812612114
root_relative_squared_error
0.296137283434817
root_relative_squared_error
0.2445390705987947
root_relative_squared_error
0.32603804963734395
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
0.9550000000000001 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1]
unweighted_recall
0.9550000000000001 [1,0.9,1,0.9,1,0.9,0.95,0.95,1,0.95]
unweighted_recall
0.9600000000000002 [1,0.85,1,0.9,1,0.9,1,0.95,1,1]
unweighted_recall
0.96 [0.95,0.95,1,0.9,0.95,0.95,1,1,1,0.9]
unweighted_recall
0.9199999999999999 [1,0.9,0.9,0.85,0.9,0.85,0.95,1,0.95,0.9]
unweighted_recall
0.95 [1,0.95,0.95,1,0.95,0.95,0.85,1,0.95,0.9]
unweighted_recall
0.9549999999999998 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85]
unweighted_recall
0.9550000000000001 [1,0.95,0.9,1,1,0.9,0.95,1,0.85,1]
unweighted_recall
0.9700000000000001 [1,1,1,0.95,1,0.9,0.9,1,0.95,1]
unweighted_recall
0.9399999999999998 [1,1,1,1,0.9,0.85,0.85,0.9,0.95,0.95]
usercpu_time_millis
7048.855287000151
usercpu_time_millis
5904.632373999448
usercpu_time_millis
7010.590791000141
usercpu_time_millis
7645.189594999465
usercpu_time_millis
6107.012374000078
usercpu_time_millis
7636.952495000514
usercpu_time_millis
7625.694089999342
usercpu_time_millis
8002.38179400003
usercpu_time_millis
7003.635084000052
usercpu_time_millis
6840.498884999761
usercpu_time_millis_testing
3.1018999998195795
usercpu_time_millis_testing
3.579100000024482
usercpu_time_millis_testing
2.919399999882444
usercpu_time_millis_testing
3.276899999946181
usercpu_time_millis_testing
3.5649999999805004
usercpu_time_millis_testing
3.1294999998863204
usercpu_time_millis_testing
3.7930999997115578
usercpu_time_millis_testing
2.884999999878346
usercpu_time_millis_testing
3.605500000048778
usercpu_time_millis_testing
3.5471000001052744
usercpu_time_millis_training
7045.753387000332
usercpu_time_millis_training
5901.053273999423
usercpu_time_millis_training
7007.671391000258
usercpu_time_millis_training
7641.912694999519
usercpu_time_millis_training
6103.447374000098
usercpu_time_millis_training
7633.822995000628
usercpu_time_millis_training
7621.900989999631
usercpu_time_millis_training
7999.496794000152
usercpu_time_millis_training
7000.0295840000035
usercpu_time_millis_training
6836.9517849996555
wall_clock_time_millis
7057.488441467285
wall_clock_time_millis
5905.267238616943
wall_clock_time_millis
7013.207912445068
wall_clock_time_millis
7655.723333358765
wall_clock_time_millis
6115.411043167114
wall_clock_time_millis
7637.702226638794
wall_clock_time_millis
7638.560771942139
wall_clock_time_millis
8037.270545959473
wall_clock_time_millis
7008.188247680664
wall_clock_time_millis
6843.835830688477
wall_clock_time_millis_testing
3.1049251556396484
wall_clock_time_millis_testing
3.584146499633789
wall_clock_time_millis_testing
2.923250198364258
wall_clock_time_millis_testing
3.2792091369628906
wall_clock_time_millis_testing
3.569364547729492
wall_clock_time_millis_testing
3.135204315185547
wall_clock_time_millis_testing
3.7963390350341797
wall_clock_time_millis_testing
2.8886795043945312
wall_clock_time_millis_testing
3.6118030548095703
wall_clock_time_millis_testing
3.5512447357177734
wall_clock_time_millis_training
7054.3835163116455
wall_clock_time_millis_training
5901.68309211731
wall_clock_time_millis_training
7010.284662246704
wall_clock_time_millis_training
7652.444124221802
wall_clock_time_millis_training
6111.841678619385
wall_clock_time_millis_training
7634.567022323608
wall_clock_time_millis_training
7634.7644329071045
wall_clock_time_millis_training
8034.381866455078
wall_clock_time_millis_training
7004.5764446258545
wall_clock_time_millis_training
6840.284585952759
weighted_recall
0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1]
weighted_recall
0.955 [1,0.9,1,0.9,1,0.9,0.95,0.95,1,0.95]
weighted_recall
0.96 [1,0.85,1,0.9,1,0.9,1,0.95,1,1]
weighted_recall
0.96 [0.95,0.95,1,0.9,0.95,0.95,1,1,1,0.9]
weighted_recall
0.92 [1,0.9,0.9,0.85,0.9,0.85,0.95,1,0.95,0.9]
weighted_recall
0.95 [1,0.95,0.95,1,0.95,0.95,0.85,1,0.95,0.9]
weighted_recall
0.955 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85]
weighted_recall
0.955 [1,0.95,0.9,1,1,0.9,0.95,1,0.85,1]
weighted_recall
0.97 [1,1,1,0.95,1,0.9,0.9,1,0.95,1]
weighted_recall
0.94 [1,1,1,1,0.9,0.85,0.85,0.9,0.95,0.95]