10551058
8323
Heinrich Peters
14
Supervised Classification
18601
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2)
8275617
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"median"
12737
verbose
0
12737
C
1.0
13106
class_weight
null
13106
dual
false
13106
fit_intercept
true
13106
intercept_scaling
1
13106
l1_ratio
null
13106
max_iter
100
13106
multi_class
"warn"
13106
n_jobs
null
13106
penalty
"l2"
13106
random_state
1
13106
solver
"warn"
13106
tol
0.0001
13106
verbose
0
13106
warm_start
false
13106
copy
true
13294
with_mean
true
13294
with_std
true
13294
memory
null
18601
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": "logisticregression", "step_name": "logisticregression"}}]
18601
verbose
false
18601
openml-python
Sklearn_0.21.2.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
22027071
description
https://api.openml.org/data/download/22027071/description.xml
-1
22027072
predictions
https://api.openml.org/data/download/22027072/predictions.arff
area_under_roc_curve
0.974706388888889 [0.999917,0.948644,0.994394,0.985711,0.962003,0.988694,0.944531,0.991019,0.99635,0.9358]
average_cost
0
f_measure
0.8170757969074977 [0.987593,0.754011,0.923457,0.8933,0.793017,0.919192,0.552764,0.862471,0.950249,0.534704]
kappa
0.7988888888888889
kb_relative_information_score
0.7949503795311176
mean_absolute_error
0.0592211308533956
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.819 [0.995,0.705,0.935,0.9,0.795,0.91,0.55,0.925,0.955,0.52]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.8168376150404169 [0.980296,0.810345,0.912195,0.8867,0.791045,0.928571,0.555556,0.80786,0.945545,0.550265]
predictive_accuracy
0.8190000000000001
prior_entropy
3.3219280948872383
relative_absolute_error
0.3290062825188543
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.162118043065743
root_relative_squared_error
0.5403934768858017
total_cost
0
unweighted_recall
0.819 [0.995,0.705,0.935,0.9,0.795,0.91,0.55,0.925,0.955,0.52]
area_under_roc_curve
0.976 [1,0.959722,0.999167,0.988611,0.964722,1,0.926389,0.989444,0.999722,0.932222]
area_under_roc_curve
0.9702222222222222 [1,0.926667,0.998611,0.9825,0.928056,0.967222,0.950833,0.993333,0.994444,0.960556]
area_under_roc_curve
0.9703888888888887 [1,0.957222,0.998056,0.949722,0.983611,0.979444,0.898333,0.9925,1,0.945]
area_under_roc_curve
0.9868611111111111 [1,0.968333,0.9825,1,0.982778,0.993056,0.983611,0.9925,0.996667,0.969167]
area_under_roc_curve
0.9708055555555555 [1,0.921944,0.998611,0.966667,0.978056,0.991944,0.956111,0.988056,1,0.906667]
area_under_roc_curve
0.9744722222222224 [1,0.951389,0.998056,0.987222,0.933333,0.996389,0.960278,0.991667,0.999167,0.927222]
area_under_roc_curve
0.9767222222222222 [1,0.949722,0.9875,0.994722,0.977778,0.99,0.954167,0.985556,0.999722,0.928056]
area_under_roc_curve
0.9821666666666666 [1,0.971944,0.998889,0.995833,0.968889,0.986389,0.946389,0.995278,0.998056,0.96]
area_under_roc_curve
0.9729166666666669 [1,0.921667,1,0.997778,0.978333,0.983889,0.936667,0.999167,1,0.911667]
area_under_roc_curve
0.9717222222222222 [1,0.965278,0.983056,0.995833,0.942222,0.999722,0.936111,0.991111,0.974444,0.929444]
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
0.8100187032073471 [0.974359,0.857143,0.95,0.842105,0.878049,0.97561,0.410256,0.85,0.930233,0.432432]
f_measure
0.8220562187043644 [0.97561,0.705882,0.952381,0.829268,0.769231,0.9,0.578947,0.837209,0.974359,0.697674]
f_measure
0.7941219758611783 [1,0.761905,0.894737,0.820513,0.818182,0.878049,0.533333,0.871795,0.97561,0.387097]
f_measure
0.8547533092306611 [1,0.756757,0.974359,0.97561,0.816327,0.857143,0.685714,0.820513,0.95,0.711111]
f_measure
0.7810736922932044 [0.97561,0.571429,0.9,0.829268,0.756757,0.871795,0.585366,0.833333,0.974359,0.512821]
f_measure
0.8150098906311404 [1,0.777778,0.904762,0.904762,0.769231,0.926829,0.512821,0.930233,0.95,0.473684]
f_measure
0.8113141096067926 [1,0.756757,0.871795,0.926829,0.8,0.926829,0.55,0.844444,0.95,0.486486]
f_measure
0.8432810158034805 [0.97561,0.833333,0.95,0.952381,0.789474,0.923077,0.666667,0.863636,0.923077,0.555556]
f_measure
0.8363040731911078 [1,0.685714,0.97561,0.97561,0.789474,0.95,0.526316,0.888889,1,0.571429]
f_measure
0.7875170492670567 [0.97561,0.8,0.863636,0.864865,0.722222,0.974359,0.473684,0.883721,0.878049,0.439024]
kappa
0.7944444444444444
kappa
0.8055555555555555
kappa
0.7777777777777778
kappa
0.8388888888888889
kappa
0.7611111111111112
kappa
0.7999999999999999
kappa
0.7944444444444444
kappa
0.8277777777777777
kappa
0.8222222222222222
kappa
0.7666666666666667
kb_relative_information_score
0.7895658653454969
kb_relative_information_score
0.787797069052844
kb_relative_information_score
0.7810548866451056
kb_relative_information_score
0.8140488877854923
kb_relative_information_score
0.7802752860713427
kb_relative_information_score
0.8107345466825759
kb_relative_information_score
0.7908788399816506
kb_relative_information_score
0.8119712742589704
kb_relative_information_score
0.799432481523477
kb_relative_information_score
0.7837446579639453
mean_absolute_error
0.06017126425854832
mean_absolute_error
0.06139877751517318
mean_absolute_error
0.06154328612094023
mean_absolute_error
0.057275139575722986
mean_absolute_error
0.06059746625447473
mean_absolute_error
0.054946338892588695
mean_absolute_error
0.05871913858866533
mean_absolute_error
0.056344037102229586
mean_absolute_error
0.05980881948189363
mean_absolute_error
0.061407040743718805
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
0.8077800600858887 [1,0.818182,0.95,0.888889,0.857143,0.952381,0.421053,0.85,0.869565,0.470588]
precision
0.8263505932155817 [0.952381,0.857143,0.909091,0.809524,0.789474,0.9,0.611111,0.782609,1,0.652174]
precision
0.7993537631958684 [1,0.727273,0.944444,0.842105,0.75,0.857143,0.48,0.894737,0.952381,0.545455]
precision
0.8697670799717346 [1,0.823529,1,0.952381,0.689655,1,0.8,0.842105,0.95,0.64]
precision
0.7858867757629368 [0.952381,0.666667,0.9,0.809524,0.823529,0.894737,0.571429,0.714286,1,0.526316]
precision
0.8142389323110147 [1,0.875,0.863636,0.863636,0.789474,0.904762,0.526316,0.869565,0.95,0.5]
precision
0.811720182809966 [1,0.823529,0.894737,0.904762,0.8,0.904762,0.55,0.76,0.95,0.529412]
precision
0.8493708703577124 [0.952381,0.9375,0.95,0.909091,0.833333,0.947368,0.6,0.791667,0.947368,0.625]
precision
0.838910533910534 [1,0.8,0.952381,0.952381,0.833333,0.95,0.555556,0.8,1,0.545455]
precision
0.790952533187188 [0.952381,0.8,0.791667,0.941176,0.8125,1,0.5,0.826087,0.857143,0.428571]
predictive_accuracy
0.815
predictive_accuracy
0.825
predictive_accuracy
0.8
predictive_accuracy
0.855
predictive_accuracy
0.785
predictive_accuracy
0.82
predictive_accuracy
0.815
predictive_accuracy
0.845
predictive_accuracy
0.84
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
relative_absolute_error
0.3342848014363799
relative_absolute_error
0.3411043195287402
relative_absolute_error
0.341907145116335
relative_absolute_error
0.31819521986512805
relative_absolute_error
0.3366525903026378
relative_absolute_error
0.3052574382921598
relative_absolute_error
0.3262174366036966
relative_absolute_error
0.31302242834572025
relative_absolute_error
0.3322712193438539
relative_absolute_error
0.3411502263539938
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
0.16313572558683448
root_mean_squared_error
0.16673008417998675
root_mean_squared_error
0.16735919855541512
root_mean_squared_error
0.1529357181199509
root_mean_squared_error
0.17067054002958826
root_mean_squared_error
0.15507833208753022
root_mean_squared_error
0.16512381922451208
root_mean_squared_error
0.15381889055017012
root_mean_squared_error
0.15795515028168894
root_mean_squared_error
0.167207353726891
root_relative_squared_error
0.5437857519561152
root_relative_squared_error
0.5557669472666228
root_relative_squared_error
0.5578639951847173
root_relative_squared_error
0.5097857270665034
root_relative_squared_error
0.5689018000986279
root_relative_squared_error
0.516927773625101
root_relative_squared_error
0.5504127307483739
root_relative_squared_error
0.5127296351672341
root_relative_squared_error
0.52651716760563
root_relative_squared_error
0.5573578457563036
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
0.8150000000000001 [0.95,0.9,0.95,0.8,0.9,1,0.4,0.85,1,0.4]
unweighted_recall
0.825 [1,0.6,1,0.85,0.75,0.9,0.55,0.9,0.95,0.75]
unweighted_recall
0.8 [1,0.8,0.85,0.8,0.9,0.9,0.6,0.85,1,0.3]
unweighted_recall
0.8550000000000001 [1,0.7,0.95,1,1,0.75,0.6,0.8,0.95,0.8]
unweighted_recall
0.7849999999999999 [1,0.5,0.9,0.85,0.7,0.85,0.6,1,0.95,0.5]
unweighted_recall
0.82 [1,0.7,0.95,0.95,0.75,0.95,0.5,1,0.95,0.45]
unweighted_recall
0.8150000000000001 [1,0.7,0.85,0.95,0.8,0.95,0.55,0.95,0.95,0.45]
unweighted_recall
0.8450000000000001 [1,0.75,0.95,1,0.75,0.9,0.75,0.95,0.9,0.5]
unweighted_recall
0.8400000000000001 [1,0.6,1,1,0.75,0.95,0.5,1,1,0.6]
unweighted_recall
0.7900000000000001 [1,0.8,0.95,0.8,0.65,0.95,0.45,0.95,0.9,0.45]
usercpu_time_millis
357.6636390062049
usercpu_time_millis
333.18508800584823
usercpu_time_millis
335.96477907849476
usercpu_time_millis
342.71742799319327
usercpu_time_millis
333.5949300089851
usercpu_time_millis
338.28313706908375
usercpu_time_millis
352.8532420168631
usercpu_time_millis
382.1320250281133
usercpu_time_millis
327.0901310024783
usercpu_time_millis
329.88246995955706
usercpu_time_millis_testing
0.7787229842506349
usercpu_time_millis_testing
0.824430026113987
usercpu_time_millis_testing
0.8248910307884216
usercpu_time_millis_testing
0.8768650004640222
usercpu_time_millis_testing
0.8495610090903938
usercpu_time_millis_testing
0.7998510263860226
usercpu_time_millis_testing
0.911083014216274
usercpu_time_millis_testing
0.917955010663718
usercpu_time_millis_testing
0.893512973561883
usercpu_time_millis_testing
0.8472710032947361
usercpu_time_millis_training
356.88491602195427
usercpu_time_millis_training
332.36065797973424
usercpu_time_millis_training
335.13988804770634
usercpu_time_millis_training
341.84056299272925
usercpu_time_millis_training
332.7453689998947
usercpu_time_millis_training
337.4832860426977
usercpu_time_millis_training
351.9421590026468
usercpu_time_millis_training
381.21407001744956
usercpu_time_millis_training
326.1966180289164
usercpu_time_millis_training
329.0351989562623
wall_clock_time_millis
358.8685989379883
wall_clock_time_millis
335.16883850097656
wall_clock_time_millis
335.97278594970703
wall_clock_time_millis
342.731237411499
wall_clock_time_millis
333.6021900177002
wall_clock_time_millis
338.2883071899414
wall_clock_time_millis
352.8742790222168
wall_clock_time_millis
382.5211524963379
wall_clock_time_millis
327.13961601257324
wall_clock_time_millis
330.244779586792
wall_clock_time_millis_testing
0.7851123809814453
wall_clock_time_millis_testing
0.8296966552734375
wall_clock_time_millis_testing
0.8301734924316406
wall_clock_time_millis_testing
0.8845329284667969
wall_clock_time_millis_testing
0.8528232574462891
wall_clock_time_millis_testing
0.8032321929931641
wall_clock_time_millis_testing
0.9143352508544922
wall_clock_time_millis_testing
0.9202957153320312
wall_clock_time_millis_testing
0.8969306945800781
wall_clock_time_millis_testing
0.8516311645507812
wall_clock_time_millis_training
358.08348655700684
wall_clock_time_millis_training
334.3391418457031
wall_clock_time_millis_training
335.1426124572754
wall_clock_time_millis_training
341.8467044830322
wall_clock_time_millis_training
332.7493667602539
wall_clock_time_millis_training
337.48507499694824
wall_clock_time_millis_training
351.9599437713623
wall_clock_time_millis_training
381.60085678100586
wall_clock_time_millis_training
326.24268531799316
wall_clock_time_millis_training
329.3931484222412
weighted_recall
0.815 [0.95,0.9,0.95,0.8,0.9,1,0.4,0.85,1,0.4]
weighted_recall
0.825 [1,0.6,1,0.85,0.75,0.9,0.55,0.9,0.95,0.75]
weighted_recall
0.8 [1,0.8,0.85,0.8,0.9,0.9,0.6,0.85,1,0.3]
weighted_recall
0.855 [1,0.7,0.95,1,1,0.75,0.6,0.8,0.95,0.8]
weighted_recall
0.785 [1,0.5,0.9,0.85,0.7,0.85,0.6,1,0.95,0.5]
weighted_recall
0.82 [1,0.7,0.95,0.95,0.75,0.95,0.5,1,0.95,0.45]
weighted_recall
0.815 [1,0.7,0.85,0.95,0.8,0.95,0.55,0.95,0.95,0.45]
weighted_recall
0.845 [1,0.75,0.95,1,0.75,0.9,0.75,0.95,0.9,0.5]
weighted_recall
0.84 [1,0.6,1,1,0.75,0.95,0.5,1,1,0.6]
weighted_recall
0.79 [1,0.8,0.95,0.8,0.65,0.95,0.45,0.95,0.9,0.45]