10576496
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)
8292778
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
0.41893294012637605
19038
loss
"deviance"
19038
max_depth
3
19038
max_features
null
19038
max_leaf_nodes
1802
19038
min_impurity_decrease
0.0
19038
min_impurity_split
null
19038
min_samples_leaf
119
19038
min_samples_split
2
19038
min_weight_fraction_leaf
0.0
19038
n_estimators
100
19038
n_iter_no_change
1
19038
random_state
52187
19038
subsample
1.0
19038
tol
0.0001
19038
validation_fraction
0.28023655397500624
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
22079259
description
https://api.openml.org/data/download/22079259/description.xml
-1
22079260
predictions
https://api.openml.org/data/download/22079260/predictions.arff
area_under_roc_curve
0.996166388888889 [0.999033,0.994569,0.999508,0.996444,0.99715,0.992514,0.993283,0.998922,0.994775,0.995464]
average_cost
0
f_measure
0.9401114372205925 [0.967419,0.921569,0.969849,0.929293,0.947368,0.910891,0.943878,0.952854,0.910891,0.947103]
kappa
0.9333333333333332
kb_relative_information_score
0.9240038085940669
mean_absolute_error
0.02059478068839761
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.94 [0.965,0.94,0.965,0.92,0.945,0.92,0.925,0.96,0.92,0.94]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9404557892735533 [0.969849,0.903846,0.974747,0.938776,0.949749,0.901961,0.963542,0.945813,0.901961,0.954315]
predictive_accuracy
0.94
prior_entropy
3.3219280948872383
relative_absolute_error
0.11441544826887208
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.09725729947482814
root_relative_squared_error
0.32419099824942216
total_cost
0
unweighted_recall
0.9399999999999998 [0.965,0.94,0.965,0.92,0.945,0.92,0.925,0.96,0.92,0.94]
area_under_roc_curve
0.9975 [0.996667,0.998056,1,1,0.999444,0.990278,0.997222,1,0.994167,0.999167]
area_under_roc_curve
0.9979444444444444 [1,0.991944,1,0.998333,1,0.993611,0.999722,0.997778,0.999167,0.998889]
area_under_roc_curve
0.9960555555555556 [0.999722,0.982222,0.999722,0.999444,1,0.988333,1,0.9975,0.996389,0.997222]
area_under_roc_curve
0.9980277777777776 [1,0.999167,1,0.996944,0.997222,0.991111,1,0.997778,0.999167,0.998889]
area_under_roc_curve
0.9962777777777778 [1,0.995,0.998056,0.990556,0.994167,0.986389,0.999722,1,0.998889,1]
area_under_roc_curve
0.9941388888888889 [1,0.994167,0.999722,0.998611,0.987778,0.989444,0.994444,0.999167,0.995278,0.982778]
area_under_roc_curve
0.9970277777777778 [0.998056,0.993333,0.999444,1,1,0.996111,1,0.999167,0.995278,0.988889]
area_under_roc_curve
0.9971388888888888 [1,0.997778,1,0.9975,0.999167,0.9975,0.997778,0.999167,0.983056,0.999444]
area_under_roc_curve
0.9970833333333333 [0.999167,1,0.999722,0.988056,0.997778,0.991111,0.996111,1,0.998889,1]
area_under_roc_curve
0.9951111111111111 [1,0.998056,1,0.998056,1,0.998333,0.9725,1,0.9925,0.991667]
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
0.944933299477587 [0.947368,0.9,1,0.974359,0.952381,0.926829,0.894737,1,0.878049,0.97561]
f_measure
0.9400459015464837 [0.97561,0.926829,0.974359,0.947368,0.974359,0.871795,0.930233,0.926829,0.95,0.923077]
f_measure
0.9353884946888797 [0.974359,0.894737,0.95,0.947368,0.97561,0.857143,1,0.923077,0.904762,0.926829]
f_measure
0.9600875076998311 [0.974359,0.952381,0.97561,0.947368,0.974359,0.95,0.97561,0.95,0.926829,0.974359]
f_measure
0.939790352993177 [0.97561,0.904762,0.923077,0.894737,0.947368,0.9,0.974359,0.97561,0.95,0.952381]
f_measure
0.9147747767943606 [0.952381,0.888889,0.974359,0.947368,0.864865,0.883721,0.864865,0.952381,0.9,0.918919]
f_measure
0.9301667244721847 [0.947368,0.864865,0.974359,0.930233,0.952381,0.923077,1,0.926829,0.863636,0.918919]
f_measure
0.9495749849921864 [1,0.95,0.97561,0.904762,0.952381,0.947368,0.974359,0.95,0.888889,0.952381]
f_measure
0.9498187211601845 [0.95,1,0.95,0.9,0.926829,0.926829,0.918919,0.97561,0.95,1]
f_measure
0.9349984094579132 [0.97561,0.930233,1,0.904762,0.947368,0.926829,0.894737,0.947368,0.9,0.923077]
kappa
0.9388888888888889
kappa
0.9333333333333332
kappa
0.9277777777777778
kappa
0.9555555555555555
kappa
0.9333333333333332
kappa
0.9055555555555556
kappa
0.9222222222222223
kappa
0.9444444444444444
kappa
0.9444444444444444
kappa
0.9277777777777778
kb_relative_information_score
0.9178155489602081
kb_relative_information_score
0.9171765723442055
kb_relative_information_score
0.9246440930744854
kb_relative_information_score
0.9476374975149865
kb_relative_information_score
0.9222767096438419
kb_relative_information_score
0.899034911520053
kb_relative_information_score
0.9211034816910467
kb_relative_information_score
0.9283452425299825
kb_relative_information_score
0.9267331421683122
kb_relative_information_score
0.9352708864932328
mean_absolute_error
0.023550385198396976
mean_absolute_error
0.023868294657461212
mean_absolute_error
0.02010234249212606
mean_absolute_error
0.013604534060230149
mean_absolute_error
0.021508107255337913
mean_absolute_error
0.026917841844673173
mean_absolute_error
0.020176031754500338
mean_absolute_error
0.01891734138733655
mean_absolute_error
0.021198592324875754
mean_absolute_error
0.016104335909037912
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
0.9467821067821067 [1,0.9,1,1,0.909091,0.904762,0.944444,1,0.857143,0.952381]
precision
0.9423575242453961 [0.952381,0.904762,1,1,1,0.894737,0.869565,0.904762,0.95,0.947368]
precision
0.9380773904458115 [1,0.944444,0.95,1,0.952381,0.818182,1,0.947368,0.863636,0.904762]
precision
0.9618614718614719 [1,0.909091,0.952381,1,1,0.95,0.952381,0.95,0.904762,1]
precision
0.9419302042986253 [0.952381,0.863636,0.947368,0.944444,1,0.9,1,0.952381,0.95,0.909091]
precision
0.9226621715880029 [0.909091,0.8,1,1,0.941176,0.826087,0.941176,0.909091,0.9,1]
precision
0.9363629589551653 [1,0.941176,1,0.869565,0.909091,0.947368,1,0.904762,0.791667,1]
precision
0.9534199134199135 [1,0.95,0.952381,0.863636,0.909091,1,1,0.95,1,0.909091]
precision
0.9511904761904763 [0.95,1,0.95,0.9,0.904762,0.904762,1,0.952381,0.95,1]
precision
0.9382157303667601 [0.952381,0.869565,1,0.863636,1,0.904762,0.944444,1,0.9,0.947368]
predictive_accuracy
0.945
predictive_accuracy
0.94
predictive_accuracy
0.935
predictive_accuracy
0.96
predictive_accuracy
0.94
predictive_accuracy
0.915
predictive_accuracy
0.93
predictive_accuracy
0.95
predictive_accuracy
0.95
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
0.1308354733244278
relative_absolute_error
0.13260163698589578
relative_absolute_error
0.11167968051181157
relative_absolute_error
0.07558074477905646
relative_absolute_error
0.11948948475187741
relative_absolute_error
0.14954356580374
relative_absolute_error
0.11208906530277979
relative_absolute_error
0.10509634104075871
relative_absolute_error
0.11776995736042098
relative_absolute_error
0.0894685328279885
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
0.09564864547152277
root_mean_squared_error
0.09597376053041996
root_mean_squared_error
0.09898639169425012
root_mean_squared_error
0.07890914150142048
root_mean_squared_error
0.09951257043630712
root_mean_squared_error
0.11737708226790733
root_mean_squared_error
0.09962637888551246
root_mean_squared_error
0.09188928244897535
root_mean_squared_error
0.09116481932972578
root_mean_squared_error
0.09922211229620732
root_relative_squared_error
0.3188288182384094
root_relative_squared_error
0.31991253510140005
root_relative_squared_error
0.32995463898083394
root_relative_squared_error
0.26303047167140176
root_relative_squared_error
0.33170856812102395
root_relative_squared_error
0.3912569408930247
root_relative_squared_error
0.332087929618375
root_relative_squared_error
0.3062976081632513
root_relative_squared_error
0.3038827310990861
root_relative_squared_error
0.33074037432069125
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 [0.9,0.9,1,0.95,1,0.95,0.85,1,0.9,1]
unweighted_recall
0.9400000000000001 [1,0.95,0.95,0.9,0.95,0.85,1,0.95,0.95,0.9]
unweighted_recall
0.9349999999999999 [0.95,0.85,0.95,0.9,1,0.9,1,0.9,0.95,0.95]
unweighted_recall
0.96 [0.95,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95]
unweighted_recall
0.9400000000000001 [1,0.95,0.9,0.85,0.9,0.9,0.95,1,0.95,1]
unweighted_recall
0.915 [1,1,0.95,0.9,0.8,0.95,0.8,1,0.9,0.85]
unweighted_recall
0.93 [0.9,0.8,0.95,1,1,0.9,1,0.95,0.95,0.85]
unweighted_recall
0.9500000000000002 [1,0.95,1,0.95,1,0.9,0.95,0.95,0.8,1]
unweighted_recall
0.95 [0.95,1,0.95,0.9,0.95,0.95,0.85,1,0.95,1]
unweighted_recall
0.9350000000000002 [1,1,1,0.95,0.9,0.95,0.85,0.9,0.9,0.9]
usercpu_time_millis
2869.9559360011335
usercpu_time_millis
2575.062234000143
usercpu_time_millis
3568.7932429991633
usercpu_time_millis
3689.1380460010623
usercpu_time_millis
3717.894944001273
usercpu_time_millis
2875.7472340003005
usercpu_time_millis
3735.1856430004773
usercpu_time_millis
2866.7535349995887
usercpu_time_millis
2564.125230999707
usercpu_time_millis
4774.747564999416
usercpu_time_millis_testing
3.051499999855878
usercpu_time_millis_testing
2.8187000007164897
usercpu_time_millis_testing
3.1767999989824602
usercpu_time_millis_testing
3.380900000593101
usercpu_time_millis_testing
2.7370000007067574
usercpu_time_millis_testing
2.8720000000248547
usercpu_time_millis_testing
2.5415999998585903
usercpu_time_millis_testing
3.29169999986334
usercpu_time_millis_testing
3.279399999883026
usercpu_time_millis_testing
2.7496000002429355
usercpu_time_millis_training
2866.9044360012776
usercpu_time_millis_training
2572.2435339994263
usercpu_time_millis_training
3565.616443000181
usercpu_time_millis_training
3685.757146000469
usercpu_time_millis_training
3715.157944000566
usercpu_time_millis_training
2872.8752340002757
usercpu_time_millis_training
3732.6440430006187
usercpu_time_millis_training
2863.4618349997254
usercpu_time_millis_training
2560.845830999824
usercpu_time_millis_training
4771.997964999173
wall_clock_time_millis
2873.2264041900635
wall_clock_time_millis
2579.3185234069824
wall_clock_time_millis
3572.617530822754
wall_clock_time_millis
3690.9680366516113
wall_clock_time_millis
3728.121757507324
wall_clock_time_millis
2878.7546157836914
wall_clock_time_millis
3747.35426902771
wall_clock_time_millis
2869.1580295562744
wall_clock_time_millis
2565.38987159729
wall_clock_time_millis
4782.706499099731
wall_clock_time_millis_testing
3.0558109283447266
wall_clock_time_millis_testing
2.8228759765625
wall_clock_time_millis_testing
3.1812191009521484
wall_clock_time_millis_testing
3.3845901489257812
wall_clock_time_millis_testing
2.7403831481933594
wall_clock_time_millis_testing
2.8765201568603516
wall_clock_time_millis_testing
2.5446414947509766
wall_clock_time_millis_testing
3.2956600189208984
wall_clock_time_millis_testing
3.2851696014404297
wall_clock_time_millis_testing
2.756357192993164
wall_clock_time_millis_training
2870.1705932617188
wall_clock_time_millis_training
2576.49564743042
wall_clock_time_millis_training
3569.4363117218018
wall_clock_time_millis_training
3687.5834465026855
wall_clock_time_millis_training
3725.381374359131
wall_clock_time_millis_training
2875.878095626831
wall_clock_time_millis_training
3744.809627532959
wall_clock_time_millis_training
2865.8623695373535
wall_clock_time_millis_training
2562.1047019958496
wall_clock_time_millis_training
4779.950141906738
weighted_recall
0.945 [0.9,0.9,1,0.95,1,0.95,0.85,1,0.9,1]
weighted_recall
0.94 [1,0.95,0.95,0.9,0.95,0.85,1,0.95,0.95,0.9]
weighted_recall
0.935 [0.95,0.85,0.95,0.9,1,0.9,1,0.9,0.95,0.95]
weighted_recall
0.96 [0.95,1,1,0.9,0.95,0.95,1,0.95,0.95,0.95]
weighted_recall
0.94 [1,0.95,0.9,0.85,0.9,0.9,0.95,1,0.95,1]
weighted_recall
0.915 [1,1,0.95,0.9,0.8,0.95,0.8,1,0.9,0.85]
weighted_recall
0.93 [0.9,0.8,0.95,1,1,0.9,1,0.95,0.95,0.85]
weighted_recall
0.95 [1,0.95,1,0.95,1,0.9,0.95,0.95,0.8,1]
weighted_recall
0.95 [0.95,1,0.95,0.9,0.95,0.95,0.85,1,0.95,1]
weighted_recall
0.935 [1,1,1,0.95,0.9,0.95,0.85,0.9,0.9,0.9]