10326854
8323
Heinrich Peters
14
Supervised Classification
16345
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)
8182524
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"most_frequent"
12737
verbose
0
12737
copy
true
13294
with_mean
true
13294
with_std
true
13294
C
42.8718089702478
13389
cache_size
200
13389
class_weight
null
13389
coef0
-0.6390272054347252
13389
decision_function_shape
"ovr"
13389
degree
5
13389
gamma
0.02965844567448009
13389
kernel
"rbf"
13389
max_iter
-1
13389
probability
false
13389
random_state
5071
13389
shrinking
true
13389
tol
0.001
13389
verbose
false
13389
memory
null
16345
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
16345
verbose
false
16345
openml-python
Sklearn_0.21.2.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
21575394
description
https://api.openml.org/data/download/21575394/description.xml
-1
21575395
predictions
https://api.openml.org/data/download/21575395/predictions.arff
area_under_roc_curve
0.9050000000000001 [0.9875,0.878611,0.973889,0.942778,0.918611,0.972778,0.731111,0.949444,0.986389,0.708889]
average_cost
0
f_measure
0.8286786260982013 [0.987342,0.785894,0.964467,0.90404,0.848635,0.936275,0.509804,0.88835,0.977444,0.484536]
kappa
0.8099999999999999
kb_relative_information_score
0.8211754691141314
mean_absolute_error
0.034200000000000216
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.8288265729456434 [1,0.791878,0.979381,0.913265,0.842365,0.918269,0.5,0.863208,0.979899,0.5]
predictive_accuracy
0.8290000000000001
prior_entropy
3.3219280948872383
recall
0.829 [0.975,0.78,0.95,0.895,0.855,0.955,0.52,0.915,0.975,0.47]
relative_absolute_error
0.18999999999999534
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.18493242008906988
root_relative_squared_error
0.6164414002968902
total_cost
0
area_under_roc_curve
0.8972222222222223 [0.975,0.9,0.972222,0.925,0.916667,0.972222,0.697222,0.869444,0.997222,0.747222]
area_under_roc_curve
0.8916666666666666 [0.975,0.888889,0.975,0.916667,0.883333,0.947222,0.697222,0.913889,0.975,0.744444]
area_under_roc_curve
0.9027777777777779 [0.95,0.858333,1,0.922222,0.961111,0.969444,0.722222,0.919444,1,0.725]
area_under_roc_curve
0.9333333333333332 [1,0.844444,0.975,0.966667,0.991667,0.972222,0.877778,0.966667,0.975,0.763889]
area_under_roc_curve
0.886111111111111 [1,0.808333,0.95,0.894444,0.919444,0.991667,0.691667,0.936111,1,0.669444]
area_under_roc_curve
0.9138888888888889 [1,0.95,1,0.897222,0.883333,0.969444,0.747222,0.994444,1,0.697222]
area_under_roc_curve
0.911111111111111 [0.975,0.863889,0.95,0.966667,0.894444,0.963889,0.869444,0.988889,0.997222,0.641667]
area_under_roc_curve
0.9166666666666665 [1,0.891667,0.972222,0.994444,0.897222,1,0.744444,0.941667,0.972222,0.752778]
area_under_roc_curve
0.9222222222222222 [1,0.891667,1,0.997222,0.969444,0.975,0.608333,0.997222,1,0.783333]
area_under_roc_curve
0.875 [1,0.888889,0.944444,0.947222,0.869444,0.966667,0.655556,0.966667,0.947222,0.563889]
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
0.8166952722360993 [0.974359,0.73913,0.95,0.918919,0.85,0.95,0.461538,0.810811,0.97561,0.536585]
f_measure
0.807267488608952 [0.974359,0.8,0.974359,0.85,0.761905,0.923077,0.461538,0.829268,0.974359,0.52381]
f_measure
0.8248893596775495 [0.947368,0.731707,1,0.894737,0.863636,0.926829,0.5,0.871795,1,0.512821]
f_measure
0.8772096250003227 [1,0.777778,0.974359,0.904762,0.930233,0.95,0.727273,0.904762,0.974359,0.628571]
f_measure
0.7944657883637494 [1,0.666667,0.947368,0.842105,0.871795,0.930233,0.439024,0.837209,1,0.410256]
f_measure
0.8451472095888013 [1,0.947368,1,0.864865,0.761905,0.926829,0.536585,0.952381,1,0.461538]
f_measure
0.8300891095261265 [0.974359,0.769231,0.947368,0.904762,0.842105,0.883721,0.680851,0.909091,0.97561,0.413793]
f_measure
0.8503719506158529 [1,0.820513,0.95,0.952381,0.864865,1,0.52381,0.878049,0.95,0.564103]
f_measure
0.8537167887187558 [1,0.820513,1,0.97561,0.926829,0.974359,0.322581,0.97561,1,0.541667]
f_measure
0.7746341046341045 [1,0.8,0.9,0.923077,0.810811,0.904762,0.363636,0.904762,0.923077,0.216216]
kappa
0.7944444444444444
kappa
0.7833333333333334
kappa
0.8055555555555555
kappa
0.8666666666666667
kappa
0.7722222222222223
kappa
0.8277777777777777
kappa
0.8222222222222222
kappa
0.8333333333333333
kappa
0.8444444444444444
kappa
0.75
kb_relative_information_score
0.8065348642462777
kb_relative_information_score
0.7960772893406711
kb_relative_information_score
0.8169924391518844
kb_relative_information_score
0.8745091011327207
kb_relative_information_score
0.7856197144350645
kb_relative_information_score
0.8379075889630976
kb_relative_information_score
0.8326788015102943
kb_relative_information_score
0.8431363764159009
kb_relative_information_score
0.8535939513215075
kb_relative_information_score
0.7647045646238513
mean_absolute_error
0.03700000000000002
mean_absolute_error
0.03900000000000002
mean_absolute_error
0.03500000000000002
mean_absolute_error
0.024000000000000007
mean_absolute_error
0.041000000000000016
mean_absolute_error
0.031000000000000014
mean_absolute_error
0.032000000000000015
mean_absolute_error
0.030000000000000013
mean_absolute_error
0.02800000000000001
mean_absolute_error
0.045
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
0.8236073781739417 [1,0.653846,0.95,1,0.85,0.95,0.473684,0.882353,0.952381,0.52381]
precision
0.8107849168375484 [1,0.8,1,0.85,0.727273,0.947368,0.473684,0.809524,1,0.5]
precision
0.8276211361737676 [1,0.714286,1,0.944444,0.791667,0.904762,0.5,0.894737,1,0.526316]
precision
0.8821837944664032 [1,0.875,1,0.863636,0.869565,0.95,0.666667,0.863636,1,0.733333]
precision
0.7969634230503796 [1,0.684211,1,0.888889,0.894737,0.869565,0.428571,0.782609,1,0.421053]
precision
0.8479795746049618 [1,1,1,0.941176,0.727273,0.904762,0.52381,0.909091,1,0.473684]
precision
0.8413059438231062 [1,0.789474,1,0.863636,0.888889,0.826087,0.592593,0.833333,0.952381,0.666667]
precision
0.8528462868400949 [1,0.842105,0.95,0.909091,0.941176,1,0.5,0.857143,0.95,0.578947]
precision
0.8570460241512872 [1,0.842105,1,0.952381,0.904762,1,0.454545,0.952381,1,0.464286]
precision
0.7772989961534854 [1,0.8,0.9,0.947368,0.882353,0.863636,0.333333,0.863636,0.947368,0.235294]
predictive_accuracy
0.815
predictive_accuracy
0.805
predictive_accuracy
0.825
predictive_accuracy
0.88
predictive_accuracy
0.795
predictive_accuracy
0.845
predictive_accuracy
0.84
predictive_accuracy
0.85
predictive_accuracy
0.86
predictive_accuracy
0.775
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
recall
0.815 [0.95,0.85,0.95,0.85,0.85,0.95,0.45,0.75,1,0.55]
recall
0.805 [0.95,0.8,0.95,0.85,0.8,0.9,0.45,0.85,0.95,0.55]
recall
0.825 [0.9,0.75,1,0.85,0.95,0.95,0.5,0.85,1,0.5]
recall
0.88 [1,0.7,0.95,0.95,1,0.95,0.8,0.95,0.95,0.55]
recall
0.795 [1,0.65,0.9,0.8,0.85,1,0.45,0.9,1,0.4]
recall
0.845 [1,0.9,1,0.8,0.8,0.95,0.55,1,1,0.45]
recall
0.84 [0.95,0.75,0.9,0.95,0.8,0.95,0.8,1,1,0.3]
recall
0.85 [1,0.8,0.95,1,0.8,1,0.55,0.9,0.95,0.55]
recall
0.86 [1,0.8,1,1,0.95,0.95,0.25,1,1,0.65]
recall
0.775 [1,0.8,0.9,0.9,0.75,0.95,0.4,0.95,0.9,0.2]
relative_absolute_error
0.20555555555555588
relative_absolute_error
0.21666666666666703
relative_absolute_error
0.19444444444444475
relative_absolute_error
0.13333333333333353
relative_absolute_error
0.2277777777777781
relative_absolute_error
0.1722222222222225
relative_absolute_error
0.17777777777777806
relative_absolute_error
0.16666666666666693
relative_absolute_error
0.15555555555555578
relative_absolute_error
0.2500000000000003
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
0.19235384061671348
root_mean_squared_error
0.19748417658131504
root_mean_squared_error
0.1870828693386971
root_mean_squared_error
0.1549193338482967
root_mean_squared_error
0.20248456731316591
root_mean_squared_error
0.17606816861659014
root_mean_squared_error
0.1788854381999832
root_mean_squared_error
0.17320508075688776
root_mean_squared_error
0.16733200530681513
root_mean_squared_error
0.21213203435596426
root_relative_squared_error
0.6411794687223786
root_relative_squared_error
0.6582805886043839
root_relative_squared_error
0.6236095644623241
root_relative_squared_error
0.5163977794943226
root_relative_squared_error
0.6749485577105534
root_relative_squared_error
0.5868938953886341
root_relative_squared_error
0.5962847939999444
root_relative_squared_error
0.5773502691896262
root_relative_squared_error
0.5577733510227175
root_relative_squared_error
0.707106781186548
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
usercpu_time_millis
962.173988998984
usercpu_time_millis
955.2303530072095
usercpu_time_millis
965.11114200257
usercpu_time_millis
963.4893590045976
usercpu_time_millis
954.3371149993618
usercpu_time_millis
947.7891709975665
usercpu_time_millis
955.1284259941895
usercpu_time_millis
967.8108080042875
usercpu_time_millis
962.8612340020481
usercpu_time_millis
947.1660869967309
usercpu_time_millis_testing
54.56982200121274
usercpu_time_millis_testing
54.532737005501986
usercpu_time_millis_testing
54.76169499888783
usercpu_time_millis_testing
54.753757001890335
usercpu_time_millis_testing
54.26296500081662
usercpu_time_millis_testing
53.97351000283379
usercpu_time_millis_testing
55.47953299537767
usercpu_time_millis_testing
54.3459270047606
usercpu_time_millis_testing
53.68409099901328
usercpu_time_millis_testing
54.79490799916675
usercpu_time_millis_training
907.6041669977712
usercpu_time_millis_training
900.6976160017075
usercpu_time_millis_training
910.3494470036821
usercpu_time_millis_training
908.7356020027073
usercpu_time_millis_training
900.0741499985452
usercpu_time_millis_training
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usercpu_time_millis_training
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usercpu_time_millis_training
913.4648809995269
usercpu_time_millis_training
909.1771430030349
usercpu_time_millis_training
892.3711789975641
wall_clock_time_millis
962.5377655029297
wall_clock_time_millis
987.6976013183594
wall_clock_time_millis
1028.883934020996
wall_clock_time_millis
1021.7721462249756
wall_clock_time_millis
1009.6695423126221
wall_clock_time_millis
979.8824787139893
wall_clock_time_millis
995.2154159545898
wall_clock_time_millis
1019.9098587036133
wall_clock_time_millis
1071.0597038269043
wall_clock_time_millis
1059.237003326416
wall_clock_time_millis_testing
54.58569526672363
wall_clock_time_millis_testing
54.59260940551758
wall_clock_time_millis_testing
54.77786064147949
wall_clock_time_millis_testing
54.76880073547363
wall_clock_time_millis_testing
54.279327392578125
wall_clock_time_millis_testing
53.987979888916016
wall_clock_time_millis_testing
55.49478530883789
wall_clock_time_millis_testing
98.36053848266602
wall_clock_time_millis_testing
53.707122802734375
wall_clock_time_millis_testing
54.810285568237305
wall_clock_time_millis_training
907.952070236206
wall_clock_time_millis_training
933.1049919128418
wall_clock_time_millis_training
974.1060733795166
wall_clock_time_millis_training
967.003345489502
wall_clock_time_millis_training
955.390214920044
wall_clock_time_millis_training
925.8944988250732
wall_clock_time_millis_training
939.720630645752
wall_clock_time_millis_training
921.5493202209473
wall_clock_time_millis_training
1017.3525810241699
wall_clock_time_millis_training
1004.4267177581787