10576538
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)
8292820
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
0.6700200803375781
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1026
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
94
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
14
19038
random_state
45180
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.34720605076359207
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
22079343
description
https://api.openml.org/data/download/22079343/description.xml
-1
22079344
predictions
https://api.openml.org/data/download/22079344/predictions.arff
area_under_roc_curve
0.9971008333333333 [0.998333,0.995578,0.999511,0.996544,0.9969,0.995761,0.997547,0.997711,0.996431,0.996692]
average_cost
0
f_measure
0.9470547509053177 [0.958231,0.933333,0.984925,0.942065,0.950495,0.905941,0.954082,0.965,0.941476,0.935]
kappa
0.941111111111111
kb_relative_information_score
0.9440652196747815
mean_absolute_error
0.012736926113880685
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.947 [0.975,0.945,0.98,0.935,0.96,0.915,0.935,0.965,0.925,0.935]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9473860623847543 [0.942029,0.921951,0.989899,0.949239,0.941176,0.897059,0.973958,0.965,0.958549,0.935]
predictive_accuracy
0.9470000000000001
prior_entropy
3.3219280948872383
relative_absolute_error
0.07076070063266829
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.09381146154420977
root_relative_squared_error
0.31270487181402773
total_cost
0
unweighted_recall
0.9470000000000001 [0.975,0.945,0.98,0.935,0.96,0.915,0.935,0.965,0.925,0.935]
area_under_roc_curve
0.9954999999999998 [0.988333,0.995556,1,0.999167,1,0.989444,0.998333,0.999444,0.985,0.999722]
area_under_roc_curve
0.9985833333333335 [1,0.995556,1,0.998056,1,0.995556,0.998889,0.998611,1,0.999167]
area_under_roc_curve
0.9966944444444443 [0.999722,0.988611,1,1,1,0.996667,1,0.985833,0.999444,0.996667]
area_under_roc_curve
0.9984999999999999 [0.999167,0.998611,1,0.995556,0.994444,0.998056,1,1,0.999444,0.999722]
area_under_roc_curve
0.9954722222222222 [1,0.995278,0.994167,0.984444,0.991389,0.9925,0.999167,1,0.998889,0.998889]
area_under_roc_curve
0.997 [1,0.9975,1,1,0.995833,0.997222,0.996389,0.996944,0.998889,0.987222]
area_under_roc_curve
0.9975 [0.995833,0.998333,0.998611,0.999167,0.998056,0.997778,1,0.999444,0.996111,0.991667]
area_under_roc_curve
0.9981111111111108 [1,0.9925,1,1,0.997778,0.998333,0.997222,1,0.995556,0.999722]
area_under_roc_curve
0.9985833333333334 [0.999722,1,1,0.991389,1,0.995278,0.999444,1,1,1]
area_under_roc_curve
0.9966111111111112 [0.998611,0.999167,1,0.998056,0.993333,0.998333,0.986111,0.998889,0.995556,0.998056]
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
0.9396574596574596 [0.9,0.923077,1,0.974359,0.952381,0.9,0.923077,0.952381,0.918919,0.952381]
f_measure
0.9498592870544088 [1,0.9,1,0.9,1,0.871795,0.974359,0.926829,0.97561,0.95]
f_measure
0.9653765212109242 [0.97561,0.947368,1,1,0.97561,0.95,0.974359,0.947368,0.974359,0.909091]
f_measure
0.9499286112700746 [0.926829,0.9,0.952381,0.95,0.974359,0.926829,1,0.974359,0.97561,0.918919]
f_measure
0.9351019570830299 [0.97561,0.883721,0.947368,0.894737,0.894737,0.878049,0.97561,1,0.974359,0.926829]
f_measure
0.9391009729841564 [0.952381,0.952381,1,0.974359,0.95,0.926829,0.864865,0.952381,0.923077,0.894737]
f_measure
0.9500228195863626 [0.95,0.97561,0.974359,0.947368,0.952381,0.904762,1,0.95,0.926829,0.918919]
f_measure
0.9602086906258921 [1,0.95,0.974359,0.952381,0.909091,0.918919,0.974359,1,0.947368,0.97561]
f_measure
0.9600995688094532 [0.97561,0.97561,1,0.9,0.974359,0.878049,0.95,1,0.947368,1]
f_measure
0.9200431895874772 [0.926829,0.926829,1,0.926829,0.923077,0.904762,0.894737,0.947368,0.85,0.9]
kappa
0.9333333333333332
kappa
0.9444444444444444
kappa
0.961111111111111
kappa
0.9444444444444444
kappa
0.9277777777777778
kappa
0.9333333333333332
kappa
0.9444444444444444
kappa
0.9555555555555555
kappa
0.9555555555555555
kappa
0.9111111111111112
kb_relative_information_score
0.9324527096280462
kb_relative_information_score
0.9498493893879085
kb_relative_information_score
0.9561840038342381
kb_relative_information_score
0.9549792865462663
kb_relative_information_score
0.9234253324414636
kb_relative_information_score
0.9408813165051404
kb_relative_information_score
0.9386923296417039
kb_relative_information_score
0.9541804750123533
kb_relative_information_score
0.9652056853875004
kb_relative_information_score
0.9248016683628919
mean_absolute_error
0.015391819381704565
mean_absolute_error
0.010878495333718463
mean_absolute_error
0.010142911715528717
mean_absolute_error
0.01048338137456633
mean_absolute_error
0.018053367867068584
mean_absolute_error
0.013424261521314396
mean_absolute_error
0.014804499420308807
mean_absolute_error
0.009918728752039287
mean_absolute_error
0.00860030412108464
mean_absolute_error
0.015671491651473028
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
0.9422009569377992 [0.9,0.947368,1,1,0.909091,0.9,0.947368,0.909091,1,0.909091]
precision
0.950187969924812 [1,0.9,1,0.9,1,0.894737,1,0.904762,0.952381,0.95]
precision
0.9688095238095238 [0.952381,1,1,1,0.952381,0.95,1,1,1,0.833333]
precision
0.952099567099567 [0.904762,0.9,0.909091,0.95,1,0.904762,1,1,0.952381,1]
precision
0.9381642512077295 [0.952381,0.826087,1,0.944444,0.944444,0.857143,0.952381,1,1,0.904762]
precision
0.9415023968119942 [0.909091,0.909091,1,1,0.95,0.904762,0.941176,0.909091,0.947368,0.944444]
precision
0.952987012987013 [0.95,0.952381,1,1,0.909091,0.863636,1,0.95,0.904762,1]
precision
0.9644805194805195 [1,0.95,1,0.909091,0.833333,1,1,1,1,0.952381]
precision
0.9611904761904762 [0.952381,0.952381,1,0.9,1,0.857143,0.95,1,1,1]
precision
0.9219734943419153 [0.904762,0.904762,1,0.904762,0.947368,0.863636,0.944444,1,0.85,0.9]
predictive_accuracy
0.94
predictive_accuracy
0.95
predictive_accuracy
0.965
predictive_accuracy
0.95
predictive_accuracy
0.935
predictive_accuracy
0.94
predictive_accuracy
0.95
predictive_accuracy
0.96
predictive_accuracy
0.96
predictive_accuracy
0.92
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
0.08551010767613658
relative_absolute_error
0.060436085187324864
relative_absolute_error
0.05634950953071516
relative_absolute_error
0.05824100763647968
relative_absolute_error
0.10029648815038113
relative_absolute_error
0.07457923067396895
relative_absolute_error
0.08224721900171568
relative_absolute_error
0.05510404862244054
relative_absolute_error
0.047779467339359165
relative_absolute_error
0.08706384250818358
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
0.10027133059134888
root_mean_squared_error
0.09099886499615349
root_mean_squared_error
0.08168971431516067
root_mean_squared_error
0.08350394653584023
root_mean_squared_error
0.10768145548485146
root_mean_squared_error
0.09749297330497896
root_mean_squared_error
0.09598597795176679
root_mean_squared_error
0.08545936209112548
root_mean_squared_error
0.07480411596121393
root_mean_squared_error
0.113191030975106
root_relative_squared_error
0.33423776863782984
root_relative_squared_error
0.3033295499871785
root_relative_squared_error
0.27229904771720237
root_relative_squared_error
0.2783464884528009
root_relative_squared_error
0.3589381849495051
root_relative_squared_error
0.32497657768326343
root_relative_squared_error
0.31995325983922285
root_relative_squared_error
0.28486454030375175
root_relative_squared_error
0.2493470532040466
root_relative_squared_error
0.3773034365836868
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
0.9400000000000001 [0.9,0.9,1,0.95,1,0.9,0.9,1,0.85,1]
unweighted_recall
0.95 [1,0.9,1,0.9,1,0.85,0.95,0.95,1,0.95]
unweighted_recall
0.9650000000000001 [1,0.9,1,1,1,0.95,0.95,0.9,0.95,1]
unweighted_recall
0.95 [0.95,0.9,1,0.95,0.95,0.95,1,0.95,1,0.85]
unweighted_recall
0.9349999999999999 [1,0.95,0.9,0.85,0.85,0.9,1,1,0.95,0.95]
unweighted_recall
0.9400000000000001 [1,1,1,0.95,0.95,0.95,0.8,1,0.9,0.85]
unweighted_recall
0.95 [0.95,1,0.95,0.9,1,0.95,1,0.95,0.95,0.85]
unweighted_recall
0.96 [1,0.95,0.95,1,1,0.85,0.95,1,0.9,1]
unweighted_recall
0.96 [1,1,1,0.9,0.95,0.9,0.95,1,0.9,1]
unweighted_recall
0.9200000000000002 [0.95,0.95,1,0.95,0.9,0.95,0.85,0.9,0.85,0.9]
usercpu_time_millis
4114.334752002833
usercpu_time_millis
4772.937457999433
usercpu_time_millis
4479.532554999423
usercpu_time_millis
4770.227558998158
usercpu_time_millis
3806.5242470001976
usercpu_time_millis
4359.012756000084
usercpu_time_millis
3805.232647999219
usercpu_time_millis
5034.014463000858
usercpu_time_millis
4909.646963000341
usercpu_time_millis
4618.082558001333
usercpu_time_millis_testing
3.439900001467322
usercpu_time_millis_testing
2.619101000163937
usercpu_time_millis_testing
3.1333999995695194
usercpu_time_millis_testing
3.3850999989226693
usercpu_time_millis_testing
3.534699999363511
usercpu_time_millis_testing
3.387099999599741
usercpu_time_millis_testing
3.4297000001970446
usercpu_time_millis_testing
2.678999000636395
usercpu_time_millis_testing
2.7733000006264774
usercpu_time_millis_testing
2.694001001145807
usercpu_time_millis_training
4110.8948520013655
usercpu_time_millis_training
4770.318356999269
usercpu_time_millis_training
4476.399154999854
usercpu_time_millis_training
4766.8424589992355
usercpu_time_millis_training
3802.989547000834
usercpu_time_millis_training
4355.625656000484
usercpu_time_millis_training
3801.802947999022
usercpu_time_millis_training
5031.335464000222
usercpu_time_millis_training
4906.873662999715
usercpu_time_millis_training
4615.388557000188
wall_clock_time_millis
4117.8107261657715
wall_clock_time_millis
4790.0073528289795
wall_clock_time_millis
4481.820344924927
wall_clock_time_millis
4788.896799087524
wall_clock_time_millis
3813.1957054138184
wall_clock_time_millis
4366.838455200195
wall_clock_time_millis
3812.3040199279785
wall_clock_time_millis
5037.172555923462
wall_clock_time_millis
4913.449048995972
wall_clock_time_millis
4623.697519302368
wall_clock_time_millis_testing
3.4422874450683594
wall_clock_time_millis_testing
2.622842788696289
wall_clock_time_millis_testing
3.136873245239258
wall_clock_time_millis_testing
3.389120101928711
wall_clock_time_millis_testing
3.5386085510253906
wall_clock_time_millis_testing
3.3922195434570312
wall_clock_time_millis_testing
3.433704376220703
wall_clock_time_millis_testing
2.682209014892578
wall_clock_time_millis_testing
2.775430679321289
wall_clock_time_millis_testing
2.6977062225341797
wall_clock_time_millis_training
4114.368438720703
wall_clock_time_millis_training
4787.384510040283
wall_clock_time_millis_training
4478.6834716796875
wall_clock_time_millis_training
4785.507678985596
wall_clock_time_millis_training
3809.657096862793
wall_clock_time_millis_training
4363.446235656738
wall_clock_time_millis_training
3808.870315551758
wall_clock_time_millis_training
5034.490346908569
wall_clock_time_millis_training
4910.67361831665
wall_clock_time_millis_training
4620.999813079834
weighted_recall
0.94 [0.9,0.9,1,0.95,1,0.9,0.9,1,0.85,1]
weighted_recall
0.95 [1,0.9,1,0.9,1,0.85,0.95,0.95,1,0.95]
weighted_recall
0.965 [1,0.9,1,1,1,0.95,0.95,0.9,0.95,1]
weighted_recall
0.95 [0.95,0.9,1,0.95,0.95,0.95,1,0.95,1,0.85]
weighted_recall
0.935 [1,0.95,0.9,0.85,0.85,0.9,1,1,0.95,0.95]
weighted_recall
0.94 [1,1,1,0.95,0.95,0.95,0.8,1,0.9,0.85]
weighted_recall
0.95 [0.95,1,0.95,0.9,1,0.95,1,0.95,0.95,0.85]
weighted_recall
0.96 [1,0.95,0.95,1,1,0.85,0.95,1,0.9,1]
weighted_recall
0.96 [1,1,1,0.9,0.95,0.9,0.95,1,0.9,1]
weighted_recall
0.92 [0.95,0.95,1,0.95,0.9,0.95,0.85,0.9,0.85,0.9]