10363906
8323
Heinrich Peters
3481
Supervised Classification
16345
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)
8219351
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
32280.176938726683
13389
cache_size
200
13389
class_weight
null
13389
coef0
0.20529368962033878
13389
decision_function_shape
"ovr"
13389
degree
3
13389
gamma
7.680437851516324e-05
13389
kernel
"rbf"
13389
max_iter
-1
13389
probability
false
13389
random_state
1141
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.
300
isolet
https://www.openml.org/data/download/52405/phpB0xrNj
-1
21649516
description
https://api.openml.org/data/download/21649516/description.xml
-1
21649517
predictions
https://api.openml.org/data/download/21649517/predictions.arff
area_under_roc_curve
0.9835271620565439 [0.997866,0.957532,0.994466,0.968599,0.973466,0.978999,0.977733,0.991667,0.995,0.989733,0.994667,0.998133,0.963483,0.965399,0.998267,0.958933,0.999733,0.9998,0.981066,0.970933,0.9916,0.957066,0.996667,0.994733,1,0.976066]
average_cost
0
f_measure
0.9683477206879941 [0.986799,0.900489,0.981818,0.935323,0.9375,0.958124,0.963087,0.991597,0.994975,0.983278,0.986711,0.993355,0.929766,0.934891,0.996667,0.932432,0.993377,0.995025,0.966555,0.952862,0.989933,0.925926,0.996656,0.988353,1,0.961345]
kappa
0.9670539936305883
kb_relative_information_score
0.9679377059240875
mean_absolute_error
0.002436834680005124
mean_prior_absolute_error
0.07396449117237175
number_of_instances
7797 [300,300,300,300,300,298,300,300,300,300,300,300,299,300,300,300,300,300,300,300,300,300,300,300,300,300]
precision
0.9684896084369097 [0.977124,0.881789,0.97377,0.930693,0.925325,0.956522,0.969595,1,1,0.986577,0.983444,0.990066,0.929766,0.936455,0.996667,0.945205,0.986842,0.990099,0.969799,0.962585,0.996622,0.935374,1,0.986711,1,0.969492]
predictive_accuracy
0.9683211491599333
prior_entropy
4.700438279892712
recall
0.9683211491599333 [0.996667,0.92,0.99,0.94,0.95,0.959732,0.956667,0.983333,0.99,0.98,0.99,0.996667,0.929766,0.933333,0.996667,0.92,1,1,0.963333,0.943333,0.983333,0.916667,0.993333,0.99,1,0.953333]
relative_absolute_error
0.032946007487919614
root_mean_prior_squared_error
0.19230768465256318
root_mean_squared_error
0.049364305727976406
root_relative_squared_error
0.256694400003627
total_cost
0
area_under_roc_curve
0.9800000000000003 [0.998667,0.965333,0.982,0.981333,0.965333,0.965333,0.983333,0.983333,1,1,1,0.998667,0.966,0.966,0.983333,0.916,0.998667,1,0.982,0.982,0.966667,0.965333,1,0.966,1,0.964667]
area_under_roc_curve
0.984 [0.982,0.930667,1,0.982,0.997333,0.999333,0.982,0.983333,0.983333,0.998667,0.983333,1,0.966,0.982,1,0.932,1,0.999333,1,0.966667,0.983333,0.932667,1,1,1,1]
area_under_roc_curve
0.9806666666666668 [0.999333,0.880667,0.998667,0.949333,0.980667,0.998667,0.966667,0.983333,0.983333,0.983333,0.982667,1,0.999333,0.983333,1,0.965333,1,0.999333,0.966667,0.948667,1,0.962,1,1,1,0.966]
area_under_roc_curve
0.9846666666666668 [1,0.998,0.999333,0.95,1,0.982667,0.998667,0.983333,1,0.966667,0.998667,1,0.947333,0.931333,1,0.965333,1,1,0.982667,0.948667,1,0.95,1,0.999333,1,0.999333]
area_under_roc_curve
0.9800000000000001 [0.999333,0.962,1,0.965333,0.965333,0.964667,0.982,1,1,0.982667,0.983333,0.983333,0.948667,0.964667,0.999333,0.982667,1,1,0.948667,0.966,1,0.932667,0.983333,0.983333,1,0.982667]
area_under_roc_curve
0.9913333333333334 [1,0.998,0.983333,0.998,0.966667,0.982667,1,1,1,1,1,1,0.95,0.998,1,0.95,1,1,0.983333,0.983333,1,0.999333,1,0.999333,1,0.982667]
area_under_roc_curve
0.9833333333333333 [0.999333,0.980667,0.999333,0.965333,0.930667,0.983333,0.999333,0.983333,1,1,1,1,0.948667,0.964667,1,0.898,0.999333,1,1,0.999333,0.982667,0.966,1,1,1,0.966667]
area_under_roc_curve
0.982647085002225 [1,0.94733,0.983333,0.948665,0.980663,0.965332,0.948665,1,1,0.999332,1,1,0.997333,0.933333,1,0.999332,1,1,0.965332,0.981998,1,0.916667,1,1,1,0.981998]
area_under_roc_curve
0.9839786381842456 [1,0.965332,1,0.963329,0.981998,0.982759,0.95,1,0.983333,0.966667,0.998665,0.999332,0.963996,0.965999,1,0.981331,1,0.999332,1,0.933333,1,0.981331,1,1,1,0.966667]
area_under_roc_curve
0.9846470850022251 [1,0.94733,0.998665,0.982666,0.965999,0.964851,0.966667,1,1,1,1,1,0.948665,0.964664,1,0.999332,0.999332,1,0.981998,0.999332,0.983333,0.964664,0.983333,0.999332,1,0.95]
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
0.9614430526061292 [0.967742,0.933333,0.95082,0.935484,0.933333,0.933333,0.983051,0.983051,1,1,1,0.967742,0.949153,0.949153,0.983051,0.892857,0.967742,1,0.95082,0.95082,0.965517,0.933333,1,0.949153,1,0.918033]
f_measure
0.9691579232655477 [0.95082,0.866667,1,0.95082,0.9375,0.983607,0.95082,0.983051,0.983051,0.967742,0.983051,1,0.949153,0.95082,1,0.896552,1,0.983607,1,0.965517,0.983051,0.912281,1,1,1,1]
f_measure
0.962852830928488 [0.983607,0.807018,0.967742,0.931034,0.920635,0.967742,0.965517,0.983051,0.983051,0.983051,0.966667,1,0.983607,0.983051,1,0.933333,1,0.983607,0.965517,0.915254,1,0.861538,1,1,1,0.949153]
f_measure
0.9704043140084453 [1,0.952381,0.983607,0.947368,1,0.966667,0.967742,0.983051,1,0.965517,0.967742,1,0.885246,0.881356,1,0.933333,1,1,0.966667,0.915254,1,0.947368,1,0.983607,1,0.983607]
f_measure
0.9617864845151891 [0.983607,0.861538,1,0.933333,0.933333,0.918033,0.95082,1,1,0.966667,0.983051,0.983051,0.915254,0.918033,0.983607,0.966667,1,1,0.915254,0.949153,1,0.912281,0.983051,0.983051,1,0.966667]
f_measure
0.9833498435033748 [1,0.952381,0.983051,0.952381,0.965517,0.966667,1,1,1,1,1,1,0.947368,0.952381,1,0.947368,1,1,0.983051,0.983051,1,0.983607,1,0.983607,1,0.966667]
f_measure
0.9677499284686752 [0.983607,0.920635,0.983607,0.933333,0.866667,0.983051,0.983607,0.983051,1,1,1,1,0.915254,0.918033,1,0.842105,0.983607,1,1,0.983607,0.966667,0.949153,1,1,1,0.965517]
f_measure
0.9665053664796811 [1,0.885246,0.983051,0.915254,0.920635,0.933333,0.915254,1,1,0.983607,1,1,0.935484,0.928571,1,0.983607,1,1,0.933333,0.95082,1,0.909091,1,1,1,0.95082]
f_measure
0.969361071278465 [1,0.933333,1,0.888889,0.95082,0.982456,0.947368,1,0.983051,0.965517,0.967742,0.983607,0.903226,0.949153,1,0.935484,1,0.983607,1,0.928571,1,0.935484,1,1,1,0.965517]
f_measure
0.9704807287506603 [1,0.885246,0.967742,0.966667,0.949153,0.947368,0.965517,1,1,1,1,1,0.915254,0.918033,1,0.983607,0.983607,1,0.95082,0.983607,0.983051,0.918033,0.983051,0.983607,1,0.947368]
kappa
0.9600000000000001
kappa
0.968
kappa
0.9613333333333334
kappa
0.9693333333333334
kappa
0.9600000000000001
kappa
0.9826666666666666
kappa
0.9666666666666667
kappa
0.965289012586032
kappa
0.9679588139825432
kappa
0.9692938633999373
kb_relative_information_score
0.9610722696746876
kb_relative_information_score
0.9688613428105528
kb_relative_information_score
0.9623771607133473
kb_relative_information_score
0.9701549062198426
kb_relative_information_score
0.9610710125089236
kb_relative_information_score
0.9831282990773093
kb_relative_information_score
0.9675602276483497
kb_relative_information_score
0.9662207953530418
kb_relative_information_score
0.968818771083453
kb_relative_information_score
0.9701139982422632
mean_absolute_error
0.0029585798816568047
mean_absolute_error
0.002366863905325443
mean_absolute_error
0.002859960552268244
mean_absolute_error
0.002268244575936883
mean_absolute_error
0.0029585798816568047
mean_absolute_error
0.0012820512820512818
mean_absolute_error
0.0024654832347140027
mean_absolute_error
0.0025673940949935805
mean_absolute_error
0.002369902241532536
mean_absolute_error
0.0022711563148020133
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396449704142057
mean_prior_absolute_error
0.07396448587535052
mean_prior_absolute_error
0.07396447325283656
mean_prior_absolute_error
0.07396447325283656
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
780 [30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,30,30,30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
number_of_instances
779 [30,30,30,30,30,29,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30]
precision
0.9623019591678679 [0.9375,0.933333,0.935484,0.90625,0.933333,0.933333,1,1,1,1,1,0.9375,0.965517,0.965517,1,0.961538,0.9375,1,0.935484,0.935484,1,0.933333,1,0.965517,1,0.903226]
precision
0.9700380998305981 [0.935484,0.866667,1,0.935484,0.882353,0.967742,0.935484,1,1,0.9375,1,1,0.965517,0.935484,1,0.928571,1,0.967742,1,1,1,0.962963,1,1,1,1]
precision
0.9642193452121148 [0.967742,0.851852,0.9375,0.964286,0.878788,0.9375,1,1,1,1,0.966667,1,0.967742,1,1,0.933333,1,0.967742,1,0.931034,1,0.8,1,1,1,0.965517]
precision
0.9712514358092778 [1,0.909091,0.967742,1,1,0.966667,0.9375,1,1,1,0.9375,1,0.870968,0.896552,1,0.933333,1,1,0.966667,0.931034,1,1,1,0.967742,1,0.967742]
precision
0.9628705842832651 [0.967742,0.8,1,0.933333,0.933333,0.903226,0.935484,1,1,0.966667,1,1,0.931034,0.903226,0.967742,0.966667,1,1,0.931034,0.965517,1,0.962963,1,1,1,0.966667]
precision
0.984464997368223 [1,0.909091,1,0.909091,1,0.966667,1,1,1,1,1,1,1,0.909091,1,1,1,1,1,1,1,0.967742,1,0.967742,1,0.966667]
precision
0.9681857939366283 [0.967742,0.878788,0.967742,0.933333,0.866667,1,0.967742,1,1,1,1,1,0.931034,0.903226,1,0.888889,0.967742,1,1,0.967742,0.966667,0.965517,1,1,1,1]
precision
0.9679501084199784 [1,0.870968,1,0.931034,0.878788,0.933333,0.931034,1,1,0.967742,1,1,0.878788,1,1,0.967742,1,1,0.933333,0.935484,1,1,1,1,1,0.935484]
precision
0.9708589152169309 [1,0.933333,1,0.848485,0.935484,1,1,1,1,1,0.9375,0.967742,0.875,0.965517,1,0.90625,1,0.967742,1,1,1,0.90625,1,1,1,1]
precision
0.9711193407839303 [1,0.870968,0.9375,0.966667,0.965517,0.964286,1,1,1,1,1,1,0.931034,0.903226,1,0.967742,0.967742,1,0.935484,0.967742,1,0.903226,1,0.967742,1,1]
predictive_accuracy
0.9615384615384616
predictive_accuracy
0.9692307692307692
predictive_accuracy
0.9628205128205128
predictive_accuracy
0.9705128205128206
predictive_accuracy
0.9615384615384616
predictive_accuracy
0.9833333333333333
predictive_accuracy
0.967948717948718
predictive_accuracy
0.9666238767650834
predictive_accuracy
0.9691912708600771
predictive_accuracy
0.9704749679075738
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700441149362989
prior_entropy
4.700435698259304
prior_entropy
4.700429514669705
prior_entropy
4.700429514669705
recall
0.9615384615384616 [1,0.933333,0.966667,0.966667,0.933333,0.933333,0.966667,0.966667,1,1,1,1,0.933333,0.933333,0.966667,0.833333,1,1,0.966667,0.966667,0.933333,0.933333,1,0.933333,1,0.933333]
recall
0.9692307692307692 [0.966667,0.866667,1,0.966667,1,1,0.966667,0.966667,0.966667,1,0.966667,1,0.933333,0.966667,1,0.866667,1,1,1,0.933333,0.966667,0.866667,1,1,1,1]
recall
0.9628205128205128 [1,0.766667,1,0.9,0.966667,1,0.933333,0.966667,0.966667,0.966667,0.966667,1,1,0.966667,1,0.933333,1,1,0.933333,0.9,1,0.933333,1,1,1,0.933333]
recall
0.9705128205128205 [1,1,1,0.9,1,0.966667,1,0.966667,1,0.933333,1,1,0.9,0.866667,1,0.933333,1,1,0.966667,0.9,1,0.9,1,1,1,1]
recall
0.9615384615384616 [1,0.933333,1,0.933333,0.933333,0.933333,0.966667,1,1,0.966667,0.966667,0.966667,0.9,0.933333,1,0.966667,1,1,0.9,0.933333,1,0.866667,0.966667,0.966667,1,0.966667]
recall
0.9833333333333333 [1,1,0.966667,1,0.933333,0.966667,1,1,1,1,1,1,0.9,1,1,0.9,1,1,0.966667,0.966667,1,1,1,1,1,0.966667]
recall
0.967948717948718 [1,0.966667,1,0.933333,0.866667,0.966667,1,0.966667,1,1,1,1,0.9,0.933333,1,0.8,1,1,1,1,0.966667,0.933333,1,1,1,0.933333]
recall
0.9666238767650834 [1,0.9,0.966667,0.9,0.966667,0.933333,0.9,1,1,1,1,1,1,0.866667,1,1,1,1,0.933333,0.966667,1,0.833333,1,1,1,0.966667]
recall
0.9691912708600771 [1,0.933333,1,0.933333,0.966667,0.965517,0.9,1,0.966667,0.933333,1,1,0.933333,0.933333,1,0.966667,1,1,1,0.866667,1,0.966667,1,1,1,0.933333]
recall
0.9704749679075738 [1,0.9,1,0.966667,0.933333,0.931034,0.933333,1,1,1,1,1,0.9,0.933333,1,1,1,1,0.966667,1,0.966667,0.933333,0.966667,1,1,0.9]
relative_absolute_error
0.03999999999999976
relative_absolute_error
0.03199999999999979
relative_absolute_error
0.038666666666666426
relative_absolute_error
0.030666666666666467
relative_absolute_error
0.03999999999999976
relative_absolute_error
0.01733333333333323
relative_absolute_error
0.03333333333333311
relative_absolute_error
0.034711173404494554
relative_absolute_error
0.03204108861062766
relative_absolute_error
0.030706043251851507
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230769991209876
root_mean_prior_squared_error
0.19230767088031558
root_mean_prior_squared_error
0.19230763806177284
root_mean_prior_squared_error
0.19230763806177284
root_mean_squared_error
0.05439282932204212
root_mean_squared_error
0.04865042554105198
root_mean_squared_error
0.0534785990118313
root_mean_squared_error
0.04762609133591463
root_mean_squared_error
0.05439282932204212
root_mean_squared_error
0.03580574370197164
root_mean_squared_error
0.04965363264368482
root_mean_squared_error
0.050669459193813986
root_mean_squared_error
0.04868164173004579
root_mean_squared_error
0.04765665026837297
root_relative_squared_error
0.28284270129019456
root_relative_squared_error
0.2529822028098169
root_relative_squared_error
0.2780887038650852
root_relative_squared_error
0.24765566515372955
root_relative_squared_error
0.28284270129019456
root_relative_squared_error
0.186189859887763
root_relative_squared_error
0.2581988795372251
root_relative_squared_error
0.26348121716553147
root_relative_squared_error
0.2531446084029607
root_relative_squared_error
0.24781465129879426
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
12993.375389982248
usercpu_time_millis
13095.201669988455
usercpu_time_millis
12876.05010200059
usercpu_time_millis
13039.447594986996
usercpu_time_millis
12780.28623200953
usercpu_time_millis
12979.256565013202
usercpu_time_millis
12887.785089988029
usercpu_time_millis
12874.808294029208
usercpu_time_millis
12847.708666988183
usercpu_time_millis
12954.979430011008
usercpu_time_millis_testing
3456.0213339864276
usercpu_time_millis_testing
3484.7424300096463
usercpu_time_millis_testing
3424.445809010649
usercpu_time_millis_testing
3483.830974990269
usercpu_time_millis_testing
3400.4560809989925
usercpu_time_millis_testing
3474.6523899957538
usercpu_time_millis_testing
3437.0099430088885
usercpu_time_millis_testing
3454.1063320066314
usercpu_time_millis_testing
3428.87821799377
usercpu_time_millis_testing
3438.5652120108716
usercpu_time_millis_training
9537.35405599582
usercpu_time_millis_training
9610.459239978809
usercpu_time_millis_training
9451.604292989941
usercpu_time_millis_training
9555.616619996727
usercpu_time_millis_training
9379.830151010538
usercpu_time_millis_training
9504.604175017448
usercpu_time_millis_training
9450.77514697914
usercpu_time_millis_training
9420.701962022576
usercpu_time_millis_training
9418.830448994413
usercpu_time_millis_training
9516.414218000136
wall_clock_time_millis
12993.722200393677
wall_clock_time_millis
13095.523595809937
wall_clock_time_millis
12876.342296600342
wall_clock_time_millis
13039.77370262146
wall_clock_time_millis
12780.528545379639
wall_clock_time_millis
12979.515790939331
wall_clock_time_millis
12888.047456741333
wall_clock_time_millis
12875.087976455688
wall_clock_time_millis
12847.978115081787
wall_clock_time_millis
12955.309391021729
wall_clock_time_millis_testing
3456.1305046081543
wall_clock_time_millis_testing
3484.833240509033
wall_clock_time_millis_testing
3424.5247840881348
wall_clock_time_millis_testing
3483.9396476745605
wall_clock_time_millis_testing
3400.520086288452
wall_clock_time_millis_testing
3474.7188091278076
wall_clock_time_millis_testing
3437.0737075805664
wall_clock_time_millis_testing
3454.162836074829
wall_clock_time_millis_testing
3428.943395614624
wall_clock_time_millis_testing
3438.6677742004395
wall_clock_time_millis_training
9537.591695785522
wall_clock_time_millis_training
9610.690355300903
wall_clock_time_millis_training
9451.817512512207
wall_clock_time_millis_training
9555.8340549469
wall_clock_time_millis_training
9380.008459091187
wall_clock_time_millis_training
9504.796981811523
wall_clock_time_millis_training
9450.973749160767
wall_clock_time_millis_training
9420.92514038086
wall_clock_time_millis_training
9419.034719467163
wall_clock_time_millis_training
9516.641616821289