10435705
10963
Nelly Palacios
16
Supervised Classification
17488
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier)(1)
8259290
add_indicator
false
17407
copy
true
17407
fill_value
-1
17407
missing_values
NaN
17407
strategy
"constant"
17407
verbose
0
17407
memory
null
17488
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
17488
verbose
false
17488
base_score
0.5
17489
booster
"gbtree"
17489
colsample_bylevel
1
17489
colsample_bynode
1
17489
colsample_bytree
1
17489
gamma
0
17489
learning_rate
0.1
17489
max_delta_step
0
17489
max_depth
3
17489
min_child_weight
1
17489
missing
null
17489
n_estimators
100
17489
n_jobs
1
17489
nthread
null
17489
objective
"multi:softprob"
17489
random_state
42
17489
reg_alpha
0
17489
reg_lambda
1
17489
scale_pos_weight
1
17489
seed
null
17489
silent
null
17489
subsample
1
17489
verbosity
1
17489
openml-python
Sklearn_0.21.2.
16
mfeat-karhunen
https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff
-1
21794314
description
https://api.openml.org/data/download/21794314/description.xml
-1
21794315
predictions
https://api.openml.org/data/download/21794315/predictions.arff
area_under_roc_curve
0.9974958333333332 [0.999494,0.998078,0.999647,0.996469,0.997481,0.996428,0.993322,0.999469,0.99705,0.997519]
average_cost
0
f_measure
0.9515387322368043 [0.98,0.948403,0.974874,0.935,0.947891,0.915423,0.959391,0.972431,0.934343,0.947631]
kappa
0.9461111111111111
kb_relative_information_score
0.9302320753898171
mean_absolute_error
0.019742439177182547
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.9515 [0.98,0.965,0.97,0.935,0.955,0.92,0.945,0.97,0.925,0.95]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9517195277016945 [0.98,0.932367,0.979798,0.935,0.940887,0.910891,0.974227,0.974874,0.943878,0.945274]
predictive_accuracy
0.9515
prior_entropy
3.3219280948872383
relative_absolute_error
0.10968021765101078
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.08764316158154047
root_relative_squared_error
0.29214387193846375
total_cost
0
unweighted_recall
0.9514999999999999 [0.98,0.965,0.97,0.935,0.955,0.92,0.945,0.97,0.925,0.95]
area_under_roc_curve
0.9984722222222221 [0.998333,0.997778,1,0.999722,1,0.998333,0.998056,1,0.993056,0.999444]
area_under_roc_curve
0.9979722222222221 [1,0.995278,1,0.994444,1,0.996111,0.9975,0.997778,0.999722,0.998889]
area_under_roc_curve
0.9989444444444446 [1,0.999167,0.999722,0.9975,0.999444,0.996944,1,0.998889,0.998889,0.998889]
area_under_roc_curve
0.9972777777777779 [1,0.999444,1,0.995278,0.988056,0.996667,1,1,0.999444,0.993889]
area_under_roc_curve
0.9971388888888888 [1,0.996944,0.997778,0.9925,0.996389,0.991111,0.999444,1,0.997222,1]
area_under_roc_curve
0.9982222222222221 [1,0.998889,1,1,0.998333,0.993611,0.998056,0.999444,0.9975,0.996389]
area_under_roc_curve
0.9978888888888889 [0.998889,0.998611,1,0.998333,1,0.996667,0.999722,0.999722,0.9975,0.989444]
area_under_roc_curve
0.9991111111111111 [1,1,1,0.999444,0.999444,0.999167,0.996944,1,0.996111,1]
area_under_roc_curve
0.9986388888888889 [0.999722,1,0.999722,0.99,1,0.9975,1,1,0.999444,1]
area_under_roc_curve
0.9941388888888889 [1,0.999722,1,0.9975,1,0.999167,0.9525,0.999167,0.995833,0.9975]
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
0.955126364863207 [0.974359,0.923077,1,0.95,1,0.95,0.95,1,0.894737,0.909091]
f_measure
0.9501005092468506 [1,0.926829,1,0.9,0.974359,0.9,0.974359,0.923077,0.952381,0.95]
f_measure
0.9548404783064602 [0.97561,0.974359,0.95,0.923077,0.95,0.9,1,0.947368,0.97561,0.952381]
f_measure
0.9699906191369605 [0.974359,0.97561,0.97561,0.95,0.95,0.974359,0.97561,1,0.95,0.974359]
f_measure
0.9201579172458654 [0.97561,0.930233,0.918919,0.871795,0.9,0.837209,0.923077,1,0.894737,0.95]
f_measure
0.9548404783064603 [1,0.952381,0.97561,0.974359,0.95,0.9,0.923077,0.97561,0.95,0.947368]
f_measure
0.9549286112700746 [0.974359,0.95,0.974359,0.95,0.97561,0.926829,1,0.952381,0.926829,0.918919]
f_measure
0.9646596461744086 [0.97561,0.97561,0.974359,0.952381,0.952381,0.918919,0.974359,0.97561,0.947368,1]
f_measure
0.9550956735616555 [0.95,0.947368,0.97561,0.95,0.909091,0.95,0.974359,1,0.918919,0.97561]
f_measure
0.9349677181563619 [1,0.930233,1,0.926829,0.918919,0.904762,0.894737,0.947368,0.926829,0.9]
kappa
0.95
kappa
0.9444444444444444
kappa
0.95
kappa
0.9666666666666667
kappa
0.9111111111111112
kappa
0.95
kappa
0.95
kappa
0.961111111111111
kappa
0.95
kappa
0.9277777777777778
kb_relative_information_score
0.9314789040735486
kb_relative_information_score
0.9250234062637255
kb_relative_information_score
0.92812864745158
kb_relative_information_score
0.945953948865096
kb_relative_information_score
0.9068030808897636
kb_relative_information_score
0.9313525643213602
kb_relative_information_score
0.922302160553672
kb_relative_information_score
0.9430024207083341
kb_relative_information_score
0.9421665192741608
kb_relative_information_score
0.9261091014965847
mean_absolute_error
0.019436394519753496
mean_absolute_error
0.020180409469559492
mean_absolute_error
0.02072453524592801
mean_absolute_error
0.015848657460538006
mean_absolute_error
0.025319200219875503
mean_absolute_error
0.0190454915214675
mean_absolute_error
0.022063239714688983
mean_absolute_error
0.017334693002621488
mean_absolute_error
0.017260048147578505
mean_absolute_error
0.020211722469814498
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
0.9575146198830409 [1,0.947368,1,0.95,1,0.95,0.95,1,0.944444,0.833333]
precision
0.9511221234905446 [1,0.904762,1,0.9,1,0.9,1,0.947368,0.909091,0.95]
precision
0.9561221234905446 [0.952381,1,0.95,0.947368,0.95,0.9,1,1,0.952381,0.909091]
precision
0.9707142857142856 [1,0.952381,0.952381,0.95,0.95,1,0.952381,1,0.95,1]
precision
0.924110457302677 [0.952381,0.869565,1,0.894737,0.9,0.782609,0.947368,1,0.944444,0.95]
precision
0.9561221234905445 [1,0.909091,0.952381,1,0.95,0.9,0.947368,0.952381,0.95,1]
precision
0.9570995670995671 [1,0.95,1,0.95,0.952381,0.904762,1,0.909091,0.904762,1]
precision
0.9675324675324675 [0.952381,0.952381,1,0.909091,0.909091,1,1,0.952381,1,1]
precision
0.9588095238095238 [0.95,1,0.952381,0.95,0.833333,0.95,1,1,1,0.952381]
precision
0.9387169834995922 [1,0.869565,1,0.904762,1,0.863636,0.944444,1,0.904762,0.9]
predictive_accuracy
0.955
predictive_accuracy
0.95
predictive_accuracy
0.955
predictive_accuracy
0.97
predictive_accuracy
0.92
predictive_accuracy
0.955
predictive_accuracy
0.955
predictive_accuracy
0.965
predictive_accuracy
0.955
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
0.10797996955418622
relative_absolute_error
0.11211338594199731
relative_absolute_error
0.11513630692182242
relative_absolute_error
0.08804809700298902
relative_absolute_error
0.14066222344375295
relative_absolute_error
0.10580828623037512
relative_absolute_error
0.12257355397049449
relative_absolute_error
0.09630385001456393
relative_absolute_error
0.09588915637543625
relative_absolute_error
0.11228734705452512
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
0.08647879449831607
root_mean_squared_error
0.09099829904875802
root_mean_squared_error
0.08694147678825169
root_mean_squared_error
0.0756231025300345
root_mean_squared_error
0.1031484702909344
root_mean_squared_error
0.08565028368237171
root_mean_squared_error
0.09055492001705721
root_mean_squared_error
0.07671732607088817
root_mean_squared_error
0.08078436366411833
root_mean_squared_error
0.09585853264280143
root_relative_squared_error
0.28826264832772036
root_relative_squared_error
0.30332766349586027
root_relative_squared_error
0.2898049226275058
root_relative_squared_error
0.2520770084334485
root_relative_squared_error
0.3438282343031148
root_relative_squared_error
0.28550094560790584
root_relative_squared_error
0.3018497333901909
root_relative_squared_error
0.25572442023629405
root_relative_squared_error
0.2692812122137279
root_relative_squared_error
0.3195284421426716
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
0.95 [1,0.95,1,0.9,0.95,0.9,0.95,0.9,1,0.95]
unweighted_recall
0.9550000000000001 [1,0.95,0.95,0.9,0.95,0.9,1,0.9,1,1]
unweighted_recall
0.97 [0.95,1,1,0.95,0.95,0.95,1,1,0.95,0.95]
unweighted_recall
0.9200000000000002 [1,1,0.85,0.85,0.9,0.9,0.9,1,0.85,0.95]
unweighted_recall
0.9550000000000001 [1,1,1,0.95,0.95,0.9,0.9,1,0.95,0.9]
unweighted_recall
0.9549999999999998 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85]
unweighted_recall
0.9650000000000001 [1,1,0.95,1,1,0.85,0.95,1,0.9,1]
unweighted_recall
0.9550000000000001 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1]
unweighted_recall
0.9349999999999999 [1,1,1,0.95,0.85,0.95,0.85,0.9,0.95,0.9]
usercpu_time_millis
5301.102793000155
usercpu_time_millis
5332.0256510000945
usercpu_time_millis
5297.54908599989
usercpu_time_millis
5299.34351299994
usercpu_time_millis
5285.119680999742
usercpu_time_millis
5327.8133640001215
usercpu_time_millis
5275.034554000058
usercpu_time_millis
5287.157053999863
usercpu_time_millis
5300.290810999968
usercpu_time_millis
5271.287406999818
usercpu_time_millis_testing
8.56788900000538
usercpu_time_millis_testing
8.616989000074682
usercpu_time_millis_testing
8.77250999997159
usercpu_time_millis_testing
8.720895999886125
usercpu_time_millis_testing
8.745649999809757
usercpu_time_millis_testing
8.703542000148445
usercpu_time_millis_testing
8.597333000125218
usercpu_time_millis_testing
8.601054999871849
usercpu_time_millis_testing
8.698847999994541
usercpu_time_millis_testing
8.555488999945737
usercpu_time_millis_training
5292.534904000149
usercpu_time_millis_training
5323.40866200002
usercpu_time_millis_training
5288.776575999918
usercpu_time_millis_training
5290.622617000054
usercpu_time_millis_training
5276.374030999932
usercpu_time_millis_training
5319.109821999973
usercpu_time_millis_training
5266.437220999933
usercpu_time_millis_training
5278.555998999991
usercpu_time_millis_training
5291.5919629999735
usercpu_time_millis_training
5262.731917999872
wall_clock_time_millis
5309.80920791626
wall_clock_time_millis
5335.055112838745
wall_clock_time_millis
5297.715187072754
wall_clock_time_millis
5299.41201210022
wall_clock_time_millis
5285.897493362427
wall_clock_time_millis
5327.876329421997
wall_clock_time_millis
5275.138378143311
wall_clock_time_millis
5287.568092346191
wall_clock_time_millis
5300.51851272583
wall_clock_time_millis
5271.34370803833
wall_clock_time_millis_testing
8.571147918701172
wall_clock_time_millis_testing
8.619308471679688
wall_clock_time_millis_testing
8.775711059570312
wall_clock_time_millis_testing
8.72349739074707
wall_clock_time_millis_testing
8.749008178710938
wall_clock_time_millis_testing
8.70656967163086
wall_clock_time_millis_testing
8.59975814819336
wall_clock_time_millis_testing
8.603572845458984
wall_clock_time_millis_testing
8.701562881469727
wall_clock_time_millis_testing
8.558034896850586
wall_clock_time_millis_training
5301.238059997559
wall_clock_time_millis_training
5326.435804367065
wall_clock_time_millis_training
5288.939476013184
wall_clock_time_millis_training
5290.688514709473
wall_clock_time_millis_training
5277.148485183716
wall_clock_time_millis_training
5319.169759750366
wall_clock_time_millis_training
5266.538619995117
wall_clock_time_millis_training
5278.964519500732
wall_clock_time_millis_training
5291.81694984436
wall_clock_time_millis_training
5262.7856731414795
weighted_recall
0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1]
weighted_recall
0.95 [1,0.95,1,0.9,0.95,0.9,0.95,0.9,1,0.95]
weighted_recall
0.955 [1,0.95,0.95,0.9,0.95,0.9,1,0.9,1,1]
weighted_recall
0.97 [0.95,1,1,0.95,0.95,0.95,1,1,0.95,0.95]
weighted_recall
0.92 [1,1,0.85,0.85,0.9,0.9,0.9,1,0.85,0.95]
weighted_recall
0.955 [1,1,1,0.95,0.95,0.9,0.9,1,0.95,0.9]
weighted_recall
0.955 [0.95,0.95,0.95,0.95,1,0.95,1,1,0.95,0.85]
weighted_recall
0.965 [1,1,0.95,1,1,0.85,0.95,1,0.9,1]
weighted_recall
0.955 [0.95,0.9,1,0.95,1,0.95,0.95,1,0.85,1]
weighted_recall
0.935 [1,1,1,0.95,0.85,0.95,0.85,0.9,0.95,0.9]