10363624
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)
8219070
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
326.31131040223244
13389
cache_size
200
13389
class_weight
null
13389
coef0
-0.5116187321824732
13389
decision_function_shape
"ovr"
13389
degree
4
13389
gamma
0.00010216486460066312
13389
kernel
"rbf"
13389
max_iter
-1
13389
probability
false
13389
random_state
35388
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
21648950
description
https://api.openml.org/data/download/21648950/description.xml
-1
21648951
predictions
https://api.openml.org/data/download/21648951/predictions.arff
area_under_roc_curve
0.983860637671383 [0.999533,0.957599,0.994466,0.966999,0.973666,0.980677,0.977733,0.991667,0.995,0.989733,0.994667,0.998133,0.96676,0.963866,0.998267,0.960533,0.999733,0.9998,0.981133,0.970933,0.9916,0.960266,0.9966,0.9948,1,0.976133]
average_cost
0
f_measure
0.9689866767831542 [0.988468,0.901961,0.981818,0.935108,0.942149,0.959866,0.963087,0.991597,0.994975,0.983278,0.986711,0.993355,0.93178,0.936242,0.996667,0.93266,0.993377,0.995025,0.968174,0.952862,0.989933,0.926421,0.994992,0.99,1,0.962963]
kappa
0.9677209195974662
kb_relative_information_score
0.968587129045606
mean_absolute_error
0.0023875060427580564
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
0.9691110316706804 [0.977199,0.884615,0.97377,0.933555,0.934426,0.956667,0.969595,1,1,0.986577,0.983444,0.990066,0.927152,0.942568,0.996667,0.942177,0.986842,0.990099,0.973064,0.962585,0.996622,0.92953,0.996656,0.99,1,0.972789]
predictive_accuracy
0.9689624214441451
prior_entropy
4.700438279892712
recall
0.9689624214441452 [1,0.92,0.99,0.936667,0.95,0.963087,0.956667,0.983333,0.99,0.98,0.99,0.996667,0.936455,0.93,0.996667,0.923333,1,1,0.963333,0.943333,0.983333,0.923333,0.993333,0.99,1,0.953333]
relative_absolute_error
0.032279084259419215
root_mean_prior_squared_error
0.19230768465256318
root_mean_squared_error
0.04886211254907074
root_relative_squared_error
0.2540829953693661
total_cost
0
area_under_roc_curve
0.9806666666666669 [0.998667,0.965333,0.982,0.981333,0.965333,0.982,0.983333,0.983333,1,1,1,0.998667,0.966,0.966,0.983333,0.916,0.998667,1,0.982667,0.982,0.966667,0.965333,1,0.966,1,0.964667]
area_under_roc_curve
0.9853333333333333 [0.998667,0.930667,1,0.982667,0.998,0.999333,0.982,0.983333,0.983333,0.998667,0.983333,1,0.966,0.982,1,0.932,1,0.999333,1,0.966667,0.983333,0.949333,1,1,1,1]
area_under_roc_curve
0.9800000000000001 [0.999333,0.880667,0.998667,0.932667,0.980667,0.998667,0.966667,0.983333,0.983333,0.983333,0.982667,1,0.999333,0.983333,1,0.964667,1,0.999333,0.966667,0.948667,1,0.962,1,1,1,0.966]
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
0.9806666666666668 [0.999333,0.962,1,0.965333,0.965333,0.964667,0.982,1,1,0.982667,0.983333,0.983333,0.948667,0.964667,0.999333,0.982667,1,1,0.948667,0.966,1,0.949333,0.983333,0.983333,1,0.983333]
area_under_roc_curve
0.9926666666666666 [1,0.998667,0.983333,0.998,0.966667,0.982667,1,1,1,1,1,1,0.966667,0.998667,1,0.966667,1,1,0.983333,0.983333,1,0.999333,1,0.999333,1,0.982667]
area_under_roc_curve
0.9826666666666667 [0.999333,0.980667,0.999333,0.965333,0.931333,0.983333,0.999333,0.983333,1,1,1,1,0.948,0.948,1,0.898,0.999333,1,1,0.999333,0.982667,0.965333,1,1,1,0.966667]
area_under_roc_curve
0.9833146417445481 [1,0.963996,0.983333,0.948665,0.981331,0.965332,0.948665,1,1,0.999332,1,1,0.997333,0.933333,1,0.999332,1,1,0.965332,0.981998,1,0.916667,1,1,1,0.981998]
area_under_roc_curve
0.9833110814419226 [1,0.948665,1,0.963329,0.981998,0.982759,0.95,1,0.983333,0.966667,0.998665,0.999332,0.963996,0.965999,1,0.981331,1,0.999332,1,0.933333,1,0.980663,1,1,1,0.966667]
area_under_roc_curve
0.9853146417445482 [1,0.94733,0.998665,0.982666,0.965999,0.964851,0.966667,1,1,1,1,1,0.965332,0.965332,1,0.999332,0.999332,1,0.981998,0.999332,0.983333,0.964664,0.982666,1,1,0.95]
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
0.9627251038881803 [0.967742,0.933333,0.95082,0.935484,0.933333,0.95082,0.983051,0.983051,1,1,1,0.967742,0.949153,0.949153,0.983051,0.892857,0.967742,1,0.966667,0.95082,0.965517,0.933333,1,0.949153,1,0.918033]
f_measure
0.9717119229299105 [0.967742,0.866667,1,0.966667,0.952381,0.983607,0.95082,0.983051,0.983051,0.967742,0.983051,1,0.949153,0.95082,1,0.896552,1,0.983607,1,0.965517,0.983051,0.931034,1,1,1,1]
f_measure
0.9615430491033986 [0.983607,0.807018,0.967742,0.912281,0.920635,0.967742,0.965517,0.983051,0.983051,0.983051,0.966667,1,0.983607,0.983051,1,0.918033,1,0.983607,0.965517,0.915254,1,0.861538,1,1,1,0.949153]
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
0.9631379445842352 [0.983607,0.861538,1,0.933333,0.933333,0.918033,0.95082,1,1,0.966667,0.983051,0.983051,0.915254,0.918033,0.983607,0.966667,1,1,0.915254,0.949153,1,0.931034,0.983051,0.983051,1,0.983051]
f_measure
0.9859275206902668 [1,0.967742,0.983051,0.952381,0.965517,0.966667,1,1,1,1,1,1,0.965517,0.967742,1,0.965517,1,1,0.983051,0.983051,1,0.983607,1,0.983607,1,0.966667]
f_measure
0.9664261989426672 [0.983607,0.920635,0.983607,0.933333,0.881356,0.983051,0.983607,0.983051,1,1,1,1,0.9,0.9,1,0.842105,0.983607,1,1,0.983607,0.966667,0.933333,1,1,1,0.965517]
f_measure
0.9677696356123546 [1,0.903226,0.983051,0.915254,0.935484,0.933333,0.915254,1,1,0.983607,1,1,0.935484,0.928571,1,0.983607,1,1,0.933333,0.95082,1,0.909091,1,1,1,0.95082]
f_measure
0.968092982201006 [1,0.915254,1,0.888889,0.95082,0.982456,0.947368,1,0.983051,0.965517,0.967742,0.983607,0.903226,0.949153,1,0.935484,1,0.983607,1,0.928571,1,0.920635,1,1,1,0.965517]
f_measure
0.9717665658877056 [1,0.885246,0.967742,0.966667,0.949153,0.947368,0.965517,1,1,1,1,1,0.933333,0.933333,1,0.983607,0.983607,1,0.95082,0.983607,0.983051,0.918033,0.966667,1,1,0.947368]
kappa
0.9613333333333334
kappa
0.9706666666666667
kappa
0.9600000000000001
kappa
0.9693333333333334
kappa
0.9613333333333334
kappa
0.9853333333333334
kappa
0.9653333333333334
kappa
0.9666240505634922
kappa
0.9666237645651492
kappa
0.9706289128173313
kb_relative_information_score
0.9623721276711269
kb_relative_information_score
0.9714560213820461
kb_relative_information_score
0.9610798214276005
kb_relative_information_score
0.9701549062198426
kb_relative_information_score
0.9623683517946702
kb_relative_information_score
0.9857242348145664
kb_relative_information_score
0.966262888362603
kb_relative_information_score
0.9675198015358574
kb_relative_information_score
0.9675197631917467
kb_relative_information_score
0.9714142649166692
mean_absolute_error
0.002859960552268244
mean_absolute_error
0.0021696252465483227
mean_absolute_error
0.0029585798816568047
mean_absolute_error
0.002268244575936883
mean_absolute_error
0.002859960552268244
mean_absolute_error
0.0010848126232741616
mean_absolute_error
0.002564102564102563
mean_absolute_error
0.002468648168263058
mean_absolute_error
0.002468648168263058
mean_absolute_error
0.0021724103880714912
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
0.9635840104499191 [0.9375,0.933333,0.935484,0.90625,0.933333,0.935484,1,1,1,1,1,0.9375,0.965517,0.965517,1,0.961538,0.9375,1,0.966667,0.935484,1,0.933333,1,0.965517,1,0.903226]
precision
0.9723942399832277 [0.9375,0.866667,1,0.966667,0.909091,0.967742,0.935484,1,1,0.9375,1,1,0.965517,0.935484,1,0.928571,1,0.967742,1,1,1,0.964286,1,1,1,1]
precision
0.9630104883580968 [0.967742,0.851852,0.9375,0.962963,0.878788,0.9375,1,1,1,1,0.966667,1,0.967742,1,1,0.903226,1,0.967742,1,0.931034,1,0.8,1,1,1,0.965517]
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
0.9642035106161914 [0.967742,0.8,1,0.933333,0.933333,0.903226,0.935484,1,1,0.966667,1,1,0.931034,0.903226,0.967742,0.966667,1,1,0.931034,0.965517,1,0.964286,1,1,1,1]
precision
0.9866503120535377 [1,0.9375,1,0.909091,1,0.966667,1,1,1,1,1,1,1,0.9375,1,1,1,1,1,1,1,0.967742,1,0.967742,1,0.966667]
precision
0.9667796731756688 [0.967742,0.878788,0.967742,0.933333,0.896552,1,0.967742,1,1,1,1,1,0.9,0.9,1,0.888889,0.967742,1,1,0.967742,0.966667,0.933333,1,1,1,1]
precision
0.9691629856706834 [1,0.875,1,0.931034,0.90625,0.933333,0.931034,1,1,0.967742,1,1,0.878788,1,1,0.967742,1,1,0.933333,0.935484,1,1,1,1,1,0.935484]
precision
0.9697127930685291 [1,0.931034,1,0.848485,0.935484,1,1,1,1,1,0.9375,0.967742,0.875,0.965517,1,0.90625,1,0.967742,1,1,1,0.878788,1,1,1,1]
precision
0.9723259303335797 [1,0.870968,0.9375,0.966667,0.965517,0.964286,1,1,1,1,1,1,0.933333,0.933333,1,0.967742,0.967742,1,0.935484,0.967742,1,0.903226,0.966667,1,1,1]
predictive_accuracy
0.9628205128205128
predictive_accuracy
0.9717948717948718
predictive_accuracy
0.9615384615384616
predictive_accuracy
0.9705128205128206
predictive_accuracy
0.9628205128205128
predictive_accuracy
0.985897435897436
predictive_accuracy
0.9666666666666667
predictive_accuracy
0.9679075738125802
predictive_accuracy
0.9679075738125802
predictive_accuracy
0.9717586649550707
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
0.9628205128205128 [1,0.933333,0.966667,0.966667,0.933333,0.966667,0.966667,0.966667,1,1,1,1,0.933333,0.933333,0.966667,0.833333,1,1,0.966667,0.966667,0.933333,0.933333,1,0.933333,1,0.933333]
recall
0.9717948717948718 [1,0.866667,1,0.966667,1,1,0.966667,0.966667,0.966667,1,0.966667,1,0.933333,0.966667,1,0.866667,1,1,1,0.933333,0.966667,0.9,1,1,1,1]
recall
0.9615384615384616 [1,0.766667,1,0.866667,0.966667,1,0.933333,0.966667,0.966667,0.966667,0.966667,1,1,0.966667,1,0.933333,1,1,0.933333,0.9,1,0.933333,1,1,1,0.933333]
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
0.9628205128205128 [1,0.933333,1,0.933333,0.933333,0.933333,0.966667,1,1,0.966667,0.966667,0.966667,0.9,0.933333,1,0.966667,1,1,0.9,0.933333,1,0.9,0.966667,0.966667,1,0.966667]
recall
0.985897435897436 [1,1,0.966667,1,0.933333,0.966667,1,1,1,1,1,1,0.933333,1,1,0.933333,1,1,0.966667,0.966667,1,1,1,1,1,0.966667]
recall
0.9666666666666667 [1,0.966667,1,0.933333,0.866667,0.966667,1,0.966667,1,1,1,1,0.9,0.9,1,0.8,1,1,1,1,0.966667,0.933333,1,1,1,0.933333]
recall
0.9679075738125802 [1,0.933333,0.966667,0.9,0.966667,0.933333,0.9,1,1,1,1,1,1,0.866667,1,1,1,1,0.933333,0.966667,1,0.833333,1,1,1,0.966667]
recall
0.9679075738125802 [1,0.9,1,0.933333,0.966667,0.965517,0.9,1,0.966667,0.933333,1,1,0.933333,0.933333,1,0.966667,1,1,1,0.866667,1,0.966667,1,1,1,0.933333]
recall
0.9717586649550706 [1,0.9,1,0.966667,0.933333,0.931034,0.933333,1,1,1,1,1,0.933333,0.933333,1,1,1,1,0.966667,1,0.966667,0.933333,0.966667,1,1,0.9]
relative_absolute_error
0.038666666666666426
relative_absolute_error
0.029333333333333145
relative_absolute_error
0.03999999999999976
relative_absolute_error
0.030666666666666467
relative_absolute_error
0.038666666666666426
relative_absolute_error
0.014666666666666576
relative_absolute_error
0.034666666666666436
relative_absolute_error
0.033376128273552456
relative_absolute_error
0.03337613396940381
relative_absolute_error
0.029370997893075356
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
0.0534785990118313
root_mean_squared_error
0.04657923621688448
root_mean_squared_error
0.05439282932204212
root_mean_squared_error
0.04762609133591463
root_mean_squared_error
0.0534785990118313
root_mean_squared_error
0.03293649379144905
root_mean_squared_error
0.05063696835418332
root_mean_squared_error
0.04968549253316362
root_mean_squared_error
0.04968549253316362
root_mean_squared_error
0.046609123442428
root_relative_squared_error
0.2780887038650852
root_relative_squared_error
0.24221201875003037
root_relative_squared_error
0.28284270129019456
root_relative_squared_error
0.24765566515372955
root_relative_squared_error
0.2780887038650852
root_relative_squared_error
0.1712697609430297
root_relative_squared_error
0.2633122250296207
root_relative_squared_error
0.2583645899600429
root_relative_squared_error
0.2583646340516319
root_relative_squared_error
0.24236751026735753
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
13161.663457998657
usercpu_time_millis
13379.356795994681
usercpu_time_millis
13226.316329004476
usercpu_time_millis
13333.08994199615
usercpu_time_millis
13252.334709017305
usercpu_time_millis
13390.491298006964
usercpu_time_millis
13260.897524000029
usercpu_time_millis
13282.160563016078
usercpu_time_millis
13216.404137012432
usercpu_time_millis
13771.564823997323
usercpu_time_millis_testing
3466.2455630023032
usercpu_time_millis_testing
3544.562750001205
usercpu_time_millis_testing
3499.4050440000137
usercpu_time_millis_testing
3549.2184109898517
usercpu_time_millis_testing
3494.3964700069046
usercpu_time_millis_testing
3544.490875006886
usercpu_time_millis_testing
3531.0904790094355
usercpu_time_millis_testing
3520.619910006644
usercpu_time_millis_testing
3518.6794540059054
usercpu_time_millis_testing
3594.1844119952293
usercpu_time_millis_training
9695.417894996353
usercpu_time_millis_training
9834.794045993476
usercpu_time_millis_training
9726.911285004462
usercpu_time_millis_training
9783.871531006298
usercpu_time_millis_training
9757.9382390104
usercpu_time_millis_training
9846.000423000078
usercpu_time_millis_training
9729.807044990594
usercpu_time_millis_training
9761.540653009433
usercpu_time_millis_training
9697.724683006527
usercpu_time_millis_training
10177.380412002094
wall_clock_time_millis
13162.017345428467
wall_clock_time_millis
13379.699230194092
wall_clock_time_millis
13226.564407348633
wall_clock_time_millis
13333.377361297607
wall_clock_time_millis
13252.621412277222
wall_clock_time_millis
13390.742540359497
wall_clock_time_millis
13261.141300201416
wall_clock_time_millis
13282.416105270386
wall_clock_time_millis
13216.651439666748
wall_clock_time_millis
13771.92735671997
wall_clock_time_millis_testing
3466.3543701171875
wall_clock_time_millis_testing
3544.661283493042
wall_clock_time_millis_testing
3499.4709491729736
wall_clock_time_millis_testing
3549.3102073669434
wall_clock_time_millis_testing
3494.4913387298584
wall_clock_time_millis_testing
3544.553279876709
wall_clock_time_millis_testing
3531.154155731201
wall_clock_time_millis_testing
3520.6868648529053
wall_clock_time_millis_testing
3518.745183944702
wall_clock_time_millis_testing
3594.3005084991455
wall_clock_time_millis_training
9695.66297531128
wall_clock_time_millis_training
9835.03794670105
wall_clock_time_millis_training
9727.09345817566
wall_clock_time_millis_training
9784.067153930664
wall_clock_time_millis_training
9758.130073547363
wall_clock_time_millis_training
9846.189260482788
wall_clock_time_millis_training
9729.987144470215
wall_clock_time_millis_training
9761.72924041748
wall_clock_time_millis_training
9697.906255722046
wall_clock_time_millis_training
10177.626848220825