10389671
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)
8232001
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"median"
12737
verbose
0
12737
copy
true
13294
with_mean
true
13294
with_std
true
13294
C
18251.600704338267
13389
cache_size
200
13389
class_weight
null
13389
coef0
0.0
13389
decision_function_shape
"ovr"
13389
degree
3
13389
gamma
9.624749700615554e-05
13389
kernel
"rbf"
13389
max_iter
-1
13389
probability
false
13389
random_state
1
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
21701051
description
https://api.openml.org/data/download/21701051/description.xml
-1
21701052
predictions
https://api.openml.org/data/download/21701052/predictions.arff
area_under_roc_curve
0.9083333333333332 [1,0.881944,0.960556,0.930833,0.8825,0.946944,0.7975,0.928611,0.984444,0.77]
average_cost
0
f_measure
0.8354425144410215 [1,0.766265,0.943878,0.877193,0.784119,0.902743,0.625917,0.876574,0.979798,0.597938]
kappa
0.8166666666666667
kb_relative_information_score
0.8274500140574947
mean_absolute_error
0.033000000000000196
mean_prior_absolute_error
0.18000000000000554
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.8363802288217859 [1,0.739535,0.963542,0.879397,0.778325,0.900498,0.61244,0.883249,0.989796,0.617021]
predictive_accuracy
0.835
prior_entropy
3.3219280948872383
recall
0.835 [1,0.795,0.925,0.875,0.79,0.905,0.64,0.87,0.97,0.58]
relative_absolute_error
0.18333333333332877
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.18165902124585004
root_relative_squared_error
0.6055300708194908
total_cost
0
area_under_roc_curve
0.9194444444444446 [1,0.952778,0.972222,0.9,0.936111,0.975,0.847222,0.897222,1,0.713889]
area_under_roc_curve
0.8972222222222223 [1,0.85,0.95,0.891667,0.880556,0.941667,0.688889,0.925,0.975,0.869444]
area_under_roc_curve
0.9138888888888888 [1,0.911111,0.975,0.922222,0.961111,0.944444,0.794444,0.947222,1,0.683333]
area_under_roc_curve
0.9361111111111111 [1,0.894444,0.975,0.986111,0.963889,0.922222,0.863889,0.897222,0.975,0.883333]
area_under_roc_curve
0.8833333333333334 [1,0.875,0.925,0.936111,0.811111,0.911111,0.727778,0.919444,1,0.727778]
area_under_roc_curve
0.9055555555555556 [1,0.858333,0.922222,0.869444,0.866667,0.963889,0.847222,0.969444,1,0.758333]
area_under_roc_curve
0.9166666666666667 [1,0.863889,0.922222,0.994444,0.886111,0.947222,0.855556,0.961111,1,0.736111]
area_under_roc_curve
0.913888888888889 [1,0.863889,0.997222,0.944444,0.813889,0.941667,0.833333,0.916667,0.947222,0.880556]
area_under_roc_curve
0.9138888888888889 [1,0.891667,0.997222,0.991667,0.841667,0.95,0.730556,0.963889,1,0.772222]
area_under_roc_curve
0.8833333333333332 [1,0.858333,0.969444,0.872222,0.863889,0.972222,0.786111,0.888889,0.947222,0.675]
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
0.8535953880857393 [1,0.808511,0.95,0.888889,0.837209,0.974359,0.666667,0.864865,1,0.545455]
f_measure
0.8146063207490747 [1,0.681818,0.947368,0.820513,0.744186,0.878049,0.5,0.918919,0.974359,0.680851]
f_measure
0.8426830238904541 [1,0.809524,0.974359,0.894737,0.863636,0.9,0.590909,0.923077,1,0.470588]
f_measure
0.885417026910295 [1,0.842105,0.974359,0.888889,0.883721,0.894737,0.769231,0.864865,0.974359,0.761905]
f_measure
0.788540011893745 [1,0.711111,0.918919,0.837209,0.684211,0.809524,0.526316,0.871795,1,0.526316]
f_measure
0.8298540113986274 [1,0.731707,0.894737,0.810811,0.789474,0.883721,0.666667,0.926829,1,0.594595]
f_measure
0.8469263941022607 [1,0.769231,0.894737,0.952381,0.780488,0.923077,0.714286,0.863636,1,0.571429]
f_measure
0.8442854978107388 [1,0.769231,0.97561,0.9,0.702703,0.878049,0.7,0.85,0.923077,0.744186]
f_measure
0.8426170354760975 [1,0.820513,0.97561,0.930233,0.756757,0.947368,0.540541,0.883721,1,0.571429]
f_measure
0.7919801532801014 [1,0.731707,0.926829,0.833333,0.769231,0.95,0.553191,0.8,0.923077,0.432432]
kappa
0.8388888888888889
kappa
0.7944444444444444
kappa
0.8277777777777777
kappa
0.8722222222222222
kappa
0.7666666666666667
kappa
0.8111111111111111
kappa
0.8333333333333333
kappa
0.8277777777777777
kappa
0.8277777777777777
kappa
0.7666666666666667
kb_relative_information_score
0.8483651638687042
kb_relative_information_score
0.8065348642462777
kb_relative_information_score
0.8379075889630976
kb_relative_information_score
0.8797378885855239
kb_relative_information_score
0.7803909269822613
kb_relative_information_score
0.8222212266046877
kb_relative_information_score
0.8431363764159009
kb_relative_information_score
0.8379075889630976
kb_relative_information_score
0.8379075889630976
kb_relative_information_score
0.7803909269822613
mean_absolute_error
0.029000000000000012
mean_absolute_error
0.03700000000000002
mean_absolute_error
0.031000000000000014
mean_absolute_error
0.023000000000000007
mean_absolute_error
0.04200000000000001
mean_absolute_error
0.034000000000000016
mean_absolute_error
0.030000000000000013
mean_absolute_error
0.031000000000000014
mean_absolute_error
0.031000000000000014
mean_absolute_error
0.04200000000000001
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
0.8669796562251806 [1,0.703704,0.95,1,0.782609,1,0.6,0.941176,1,0.692308]
precision
0.8279159553473053 [1,0.625,1,0.842105,0.695652,0.857143,0.666667,1,1,0.592593]
precision
0.8469302042986253 [1,0.772727,1,0.944444,0.791667,0.9,0.541667,0.947368,1,0.571429]
precision
0.8917343171926561 [1,0.888889,1,0.8,0.826087,0.944444,0.789474,0.941176,1,0.727273]
precision
0.7923406143818044 [1,0.64,1,0.782609,0.722222,0.772727,0.555556,0.894737,1,0.555556]
precision
0.8352324118053018 [1,0.714286,0.944444,0.882353,0.833333,0.826087,0.6,0.904762,1,0.647059]
precision
0.8492433735854789 [1,0.789474,0.944444,0.909091,0.761905,0.947368,0.681818,0.791667,1,0.666667]
precision
0.8456723971052952 [1,0.789474,0.952381,0.9,0.764706,0.857143,0.7,0.85,0.947368,0.695652]
precision
0.8447357640788787 [1,0.842105,0.952381,0.869565,0.823529,1,0.588235,0.826087,1,0.545455]
precision
0.7995459441086377 [1,0.714286,0.904762,0.9375,0.789474,0.95,0.481481,0.8,0.947368,0.470588]
predictive_accuracy
0.855
predictive_accuracy
0.815
predictive_accuracy
0.845
predictive_accuracy
0.885
predictive_accuracy
0.79
predictive_accuracy
0.83
predictive_accuracy
0.85
predictive_accuracy
0.845
predictive_accuracy
0.845
predictive_accuracy
0.79
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
0.855 [1,0.95,0.95,0.8,0.9,0.95,0.75,0.8,1,0.45]
recall
0.815 [1,0.75,0.9,0.8,0.8,0.9,0.4,0.85,0.95,0.8]
recall
0.845 [1,0.85,0.95,0.85,0.95,0.9,0.65,0.9,1,0.4]
recall
0.885 [1,0.8,0.95,1,0.95,0.85,0.75,0.8,0.95,0.8]
recall
0.79 [1,0.8,0.85,0.9,0.65,0.85,0.5,0.85,1,0.5]
recall
0.83 [1,0.75,0.85,0.75,0.75,0.95,0.75,0.95,1,0.55]
recall
0.85 [1,0.75,0.85,1,0.8,0.9,0.75,0.95,1,0.5]
recall
0.845 [1,0.75,1,0.9,0.65,0.9,0.7,0.85,0.9,0.8]
recall
0.845 [1,0.8,1,1,0.7,0.9,0.5,0.95,1,0.6]
recall
0.79 [1,0.75,0.95,0.75,0.75,0.95,0.65,0.8,0.9,0.4]
relative_absolute_error
0.16111111111111134
relative_absolute_error
0.20555555555555588
relative_absolute_error
0.1722222222222225
relative_absolute_error
0.12777777777777796
relative_absolute_error
0.23333333333333364
relative_absolute_error
0.1888888888888892
relative_absolute_error
0.16666666666666693
relative_absolute_error
0.1722222222222225
relative_absolute_error
0.1722222222222225
relative_absolute_error
0.23333333333333364
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
0.17029386365926405
root_mean_squared_error
0.19235384061671348
root_mean_squared_error
0.17606816861659014
root_mean_squared_error
0.15165750888103102
root_mean_squared_error
0.20493901531919198
root_mean_squared_error
0.1843908891458578
root_mean_squared_error
0.17320508075688776
root_mean_squared_error
0.17606816861659014
root_mean_squared_error
0.17606816861659014
root_mean_squared_error
0.20493901531919198
root_relative_squared_error
0.5676462121975472
root_relative_squared_error
0.6411794687223786
root_relative_squared_error
0.5868938953886341
root_relative_squared_error
0.505525029603437
root_relative_squared_error
0.6831300510639737
root_relative_squared_error
0.6146362971528597
root_relative_squared_error
0.5773502691896262
root_relative_squared_error
0.5868938953886341
root_relative_squared_error
0.5868938953886341
root_relative_squared_error
0.6831300510639737
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
347.62064599999576
usercpu_time_millis
326.93344500012245
usercpu_time_millis
317.09347100002105
usercpu_time_millis
324.6827730000632
usercpu_time_millis
302.4304990000246
usercpu_time_millis
316.9054470000674
usercpu_time_millis
321.8253679999634
usercpu_time_millis
318.89182000008987
usercpu_time_millis
322.5680219999276
usercpu_time_millis
326.9232220000049
usercpu_time_millis_testing
24.848611000038545
usercpu_time_millis_testing
24.0018310000778
usercpu_time_millis_testing
23.567305000028682
usercpu_time_millis_testing
23.698509000041668
usercpu_time_millis_testing
23.762028000078317
usercpu_time_millis_testing
24.473225000065213
usercpu_time_millis_testing
24.494107000009535
usercpu_time_millis_testing
24.386661999983517
usercpu_time_millis_testing
24.230228999954306
usercpu_time_millis_testing
24.01931899998999
usercpu_time_millis_training
322.7720349999572
usercpu_time_millis_training
302.93161400004465
usercpu_time_millis_training
293.5261659999924
usercpu_time_millis_training
300.98426400002154
usercpu_time_millis_training
278.6684709999463
usercpu_time_millis_training
292.4322220000022
usercpu_time_millis_training
297.3312609999539
usercpu_time_millis_training
294.50515800010635
usercpu_time_millis_training
298.3377929999733
usercpu_time_millis_training
302.9039030000149
wall_clock_time_millis
347.6560115814209
wall_clock_time_millis
326.97081565856934
wall_clock_time_millis
317.105770111084
wall_clock_time_millis
324.6943950653076
wall_clock_time_millis
302.4411201477051
wall_clock_time_millis
316.91527366638184
wall_clock_time_millis
321.85935974121094
wall_clock_time_millis
318.9046382904053
wall_clock_time_millis
322.5820064544678
wall_clock_time_millis
326.934814453125
wall_clock_time_millis_testing
24.853229522705078
wall_clock_time_millis_testing
24.00660514831543
wall_clock_time_millis_testing
23.571014404296875
wall_clock_time_millis_testing
23.701906204223633
wall_clock_time_millis_testing
23.766040802001953
wall_clock_time_millis_testing
24.477005004882812
wall_clock_time_millis_testing
24.49798583984375
wall_clock_time_millis_testing
24.391651153564453
wall_clock_time_millis_testing
24.23548698425293
wall_clock_time_millis_testing
24.023056030273438
wall_clock_time_millis_training
322.8027820587158
wall_clock_time_millis_training
302.9642105102539
wall_clock_time_millis_training
293.5347557067871
wall_clock_time_millis_training
300.992488861084
wall_clock_time_millis_training
278.6750793457031
wall_clock_time_millis_training
292.438268661499
wall_clock_time_millis_training
297.3613739013672
wall_clock_time_millis_training
294.5129871368408
wall_clock_time_millis_training
298.34651947021484
wall_clock_time_millis_training
302.91175842285156