10543468
8323
Heinrich Peters
16
Supervised Classification
18601
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2)
8275618
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"median"
12737
verbose
0
12737
C
0.001
13106
class_weight
null
13106
dual
false
13106
fit_intercept
true
13106
intercept_scaling
1
13106
l1_ratio
null
13106
max_iter
10000
13106
multi_class
"warn"
13106
n_jobs
null
13106
penalty
"l2"
13106
random_state
1
13106
solver
"lbfgs"
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.
16
mfeat-karhunen
https://www.openml.org/data/download/16/dataset_16_mfeat-karhunen.arff
-1
22011891
description
https://api.openml.org/data/download/22011891/description.xml
-1
22011892
predictions
https://api.openml.org/data/download/22011892/predictions.arff
area_under_roc_curve
0.9865999999999999 [0.991,0.989642,0.998164,0.980353,0.994636,0.979622,0.988378,0.994208,0.963781,0.986217]
average_cost
0
f_measure
0.9105341774155947 [0.955665,0.894472,0.960591,0.913706,0.902148,0.904884,0.891041,0.925373,0.858696,0.898765]
kappa
0.9011111111111112
kb_relative_information_score
0.4734562504449616
mean_absolute_error
0.13754863263475314
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.911 [0.97,0.89,0.975,0.9,0.945,0.88,0.92,0.93,0.79,0.91]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.9122328007937572 [0.941748,0.89899,0.946602,0.927835,0.863014,0.931217,0.86385,0.920792,0.940476,0.887805]
predictive_accuracy
0.9109999999999999
prior_entropy
3.3219280948872383
relative_absolute_error
0.7641590701930495
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.23395034266437081
root_relative_squared_error
0.7798344755478908
total_cost
0
unweighted_recall
0.9109999999999999 [0.97,0.89,0.975,0.9,0.945,0.88,0.92,0.93,0.79,0.91]
area_under_roc_curve
0.9825000000000002 [0.977222,0.995278,1,0.990278,0.998889,0.948056,0.991667,0.999167,0.925556,0.998889]
area_under_roc_curve
0.9858333333333333 [1,0.953333,0.998333,0.986111,0.982778,0.988056,0.989167,0.999167,0.971389,0.99]
area_under_roc_curve
0.9887777777777776 [0.998056,0.9925,1,0.981389,1,0.985278,0.996111,0.973333,0.981389,0.979722]
area_under_roc_curve
0.9850000000000001 [0.985,0.999167,1,0.969444,0.998889,0.946667,0.992778,0.998889,0.996667,0.9625]
area_under_roc_curve
0.9826388888888888 [0.998333,0.989167,0.988333,0.973056,0.9975,0.993889,0.980556,0.988333,0.926944,0.990278]
area_under_roc_curve
0.9888055555555555 [0.999444,0.991389,1,0.973333,0.990833,0.987778,0.995,0.997222,0.983056,0.97]
area_under_roc_curve
0.9891666666666667 [0.961111,0.993611,0.996944,0.998889,0.992222,0.989444,0.998611,0.997778,0.964722,0.998333]
area_under_roc_curve
0.9855555555555555 [0.989722,0.989167,0.999722,0.994167,0.996389,0.981389,0.990278,1,0.921389,0.993333]
area_under_roc_curve
0.9919444444444443 [0.996111,0.993333,1,0.965556,0.999722,0.994167,0.994444,0.998611,0.985,0.9925]
area_under_roc_curve
0.983888888888889 [1,0.996389,1,0.97,0.989167,0.980556,0.954167,0.991111,0.978889,0.978611]
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
0.8954917541807786 [0.904762,0.9,0.97561,0.9,0.909091,0.923077,0.878049,0.95,0.6875,0.926829]
f_measure
0.9152530599555706 [0.97561,0.864865,0.974359,0.918919,0.878049,0.878049,0.883721,0.904762,0.947368,0.926829]
f_measure
0.9096127265497658 [0.904762,0.926829,0.930233,0.923077,0.95,0.871795,0.95,0.918919,0.820513,0.9]
f_measure
0.9352430026114236 [0.95,0.95,0.952381,0.947368,0.974359,0.871795,0.909091,0.974359,0.923077,0.9]
f_measure
0.8793273894923823 [0.97561,0.857143,0.926829,0.85,0.926829,0.833333,0.8,0.9,0.823529,0.9]
f_measure
0.8988900706323161 [0.930233,0.871795,0.97561,0.947368,0.904762,0.926829,0.894737,0.883721,0.833333,0.820513]
f_measure
0.921859439992207 [0.974359,0.894737,0.974359,0.97561,0.808511,0.947368,0.904762,0.95,0.888889,0.9]
f_measure
0.914985983783488 [0.974359,0.85,0.95,0.9,0.883721,0.918919,0.926829,0.952381,0.888889,0.904762]
f_measure
0.9300561911344967 [0.974359,0.926829,0.97561,0.904762,0.926829,0.923077,0.974359,0.9,0.894737,0.9]
f_measure
0.905204145448048 [1,0.9,0.974359,0.871795,0.878049,0.95,0.8,0.923077,0.85,0.904762]
kappa
0.888888888888889
kappa
0.9055555555555556
kappa
0.9
kappa
0.9277777777777778
kappa
0.8666666666666667
kappa
0.888888888888889
kappa
0.9111111111111112
kappa
0.9055555555555556
kappa
0.9222222222222223
kappa
0.8944444444444445
kb_relative_information_score
0.47356463930681586
kb_relative_information_score
0.4695747206178785
kb_relative_information_score
0.47384909362081035
kb_relative_information_score
0.4869346667010705
kb_relative_information_score
0.4605290672921471
kb_relative_information_score
0.4658106668423779
kb_relative_information_score
0.47751680846184885
kb_relative_information_score
0.47871838042844905
kb_relative_information_score
0.4816790553583089
kb_relative_information_score
0.46638540581973664
mean_absolute_error
0.13706365828875827
mean_absolute_error
0.1378705954619558
mean_absolute_error
0.1377723323211303
mean_absolute_error
0.1359210618564244
mean_absolute_error
0.13892611354010576
mean_absolute_error
0.13850730056739852
mean_absolute_error
0.13734733606524846
mean_absolute_error
0.13693058292590668
mean_absolute_error
0.13681578815239007
mean_absolute_error
0.13833155716821582
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
0.902529049897471 [0.863636,0.9,0.952381,0.9,0.833333,0.947368,0.857143,0.95,0.916667,0.904762]
precision
0.920232836217491 [0.952381,0.941176,1,1,0.857143,0.857143,0.826087,0.863636,1,0.904762]
precision
0.9122174012105362 [0.863636,0.904762,0.869565,0.947368,0.95,0.894737,0.95,1,0.842105,0.9]
precision
0.9384529505582136 [0.95,0.95,0.909091,1,1,0.894737,0.833333,1,0.947368,0.9]
precision
0.888758658008658 [0.952381,0.818182,0.904762,0.85,0.904762,0.9375,0.72,0.9,1,0.9]
precision
0.9035217944399867 [0.869565,0.894737,0.952381,1,0.863636,0.904762,0.944444,0.826087,0.9375,0.842105]
precision
0.9314165464165464 [1,0.944444,1,0.952381,0.703704,1,0.863636,0.95,1,0.9]
precision
0.9203576134010918 [1,0.85,0.95,0.9,0.826087,1,0.904762,0.909091,1,0.863636]
precision
0.9317353991038202 [1,0.904762,0.952381,0.863636,0.904762,0.947368,1,0.9,0.944444,0.9]
precision
0.9062884483937116 [1,0.9,1,0.894737,0.857143,0.95,0.8,0.947368,0.85,0.863636]
predictive_accuracy
0.9
predictive_accuracy
0.915
predictive_accuracy
0.91
predictive_accuracy
0.935
predictive_accuracy
0.88
predictive_accuracy
0.9
predictive_accuracy
0.92
predictive_accuracy
0.915
predictive_accuracy
0.93
predictive_accuracy
0.905
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
0.76146476827088
relative_absolute_error
0.7659477525664219
relative_absolute_error
0.7654018462285025
relative_absolute_error
0.7551170103134698
relative_absolute_error
0.7718117418894773
relative_absolute_error
0.7694850031522149
relative_absolute_error
0.7630407559180479
relative_absolute_error
0.7607254606994824
relative_absolute_error
0.7600877119577234
relative_absolute_error
0.7685086509345332
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
0.2334543225466831
root_mean_squared_error
0.23483110281807174
root_mean_squared_error
0.2340350942408043
root_mean_squared_error
0.23089648069755586
root_mean_squared_error
0.23647850592742986
root_mean_squared_error
0.23535631380672492
root_mean_squared_error
0.23351573340460272
root_mean_squared_error
0.23309742403723058
root_mean_squared_error
0.2321994326127409
root_mean_squared_error
0.23558478105799624
root_relative_squared_error
0.7781810751556109
root_relative_squared_error
0.7827703427269063
root_relative_squared_error
0.7801169808026814
root_relative_squared_error
0.7696549356585201
root_relative_squared_error
0.7882616864247667
root_relative_squared_error
0.7845210460224169
root_relative_squared_error
0.7783857780153428
root_relative_squared_error
0.7769914134574357
root_relative_squared_error
0.7739981087091369
root_relative_squared_error
0.7852826035266546
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
0.9 [0.95,0.9,1,0.9,1,0.9,0.9,0.95,0.55,0.95]
unweighted_recall
0.915 [1,0.8,0.95,0.85,0.9,0.9,0.95,0.95,0.9,0.95]
unweighted_recall
0.9099999999999999 [0.95,0.95,1,0.9,0.95,0.85,0.95,0.85,0.8,0.9]
unweighted_recall
0.9349999999999999 [0.95,0.95,1,0.9,0.95,0.85,1,0.95,0.9,0.9]
unweighted_recall
0.8800000000000001 [1,0.9,0.95,0.85,0.95,0.75,0.9,0.9,0.7,0.9]
unweighted_recall
0.9 [1,0.85,1,0.9,0.95,0.95,0.85,0.95,0.75,0.8]
unweighted_recall
0.9200000000000002 [0.95,0.85,0.95,1,0.95,0.9,0.95,0.95,0.8,0.9]
unweighted_recall
0.9149999999999998 [0.95,0.85,0.95,0.9,0.95,0.85,0.95,1,0.8,0.95]
unweighted_recall
0.93 [0.95,0.95,1,0.95,0.95,0.9,0.95,0.9,0.85,0.9]
unweighted_recall
0.9049999999999999 [1,0.9,0.95,0.85,0.9,0.95,0.8,0.9,0.85,0.95]
usercpu_time_millis
80.38470096653327
usercpu_time_millis
80.87949999026023
usercpu_time_millis
77.96121900901198
usercpu_time_millis
73.1551100325305
usercpu_time_millis
72.04275598633103
usercpu_time_millis
72.18896396807395
usercpu_time_millis
72.17425899580121
usercpu_time_millis
76.23725599842146
usercpu_time_millis
72.29223303147592
usercpu_time_millis
72.20132197835483
usercpu_time_millis_testing
0.8264939824584872
usercpu_time_millis_testing
0.8516239759046584
usercpu_time_millis_testing
0.772833009250462
usercpu_time_millis_testing
0.8213380060624331
usercpu_time_millis_testing
0.8035639766603708
usercpu_time_millis_testing
0.7674709777347744
usercpu_time_millis_testing
0.7235149969346821
usercpu_time_millis_testing
0.8278960012830794
usercpu_time_millis_testing
0.7848460227251053
usercpu_time_millis_testing
0.7706479809712619
usercpu_time_millis_training
79.55820698407479
usercpu_time_millis_training
80.02787601435557
usercpu_time_millis_training
77.18838599976152
usercpu_time_millis_training
72.33377202646807
usercpu_time_millis_training
71.23919200967066
usercpu_time_millis_training
71.42149299033917
usercpu_time_millis_training
71.45074399886653
usercpu_time_millis_training
75.40935999713838
usercpu_time_millis_training
71.50738700875081
usercpu_time_millis_training
71.43067399738356
wall_clock_time_millis
80.39140701293945
wall_clock_time_millis
80.88374137878418
wall_clock_time_millis
77.97098159790039
wall_clock_time_millis
73.16112518310547
wall_clock_time_millis
72.04961776733398
wall_clock_time_millis
72.19386100769043
wall_clock_time_millis
72.18003273010254
wall_clock_time_millis
76.24506950378418
wall_clock_time_millis
72.29876518249512
wall_clock_time_millis
72.20959663391113
wall_clock_time_millis_testing
0.8337497711181641
wall_clock_time_millis_testing
0.8552074432373047
wall_clock_time_millis_testing
0.7793903350830078
wall_clock_time_millis_testing
0.8268356323242188
wall_clock_time_millis_testing
0.8101463317871094
wall_clock_time_millis_testing
0.7736682891845703
wall_clock_time_millis_testing
0.7266998291015625
wall_clock_time_millis_testing
0.8323192596435547
wall_clock_time_millis_testing
0.7913112640380859
wall_clock_time_millis_testing
0.7770061492919922
wall_clock_time_millis_training
79.55765724182129
wall_clock_time_millis_training
80.02853393554688
wall_clock_time_millis_training
77.19159126281738
wall_clock_time_millis_training
72.33428955078125
wall_clock_time_millis_training
71.23947143554688
wall_clock_time_millis_training
71.42019271850586
wall_clock_time_millis_training
71.45333290100098
wall_clock_time_millis_training
75.41275024414062
wall_clock_time_millis_training
71.50745391845703
wall_clock_time_millis_training
71.43259048461914
weighted_recall
0.9 [0.95,0.9,1,0.9,1,0.9,0.9,0.95,0.55,0.95]
weighted_recall
0.915 [1,0.8,0.95,0.85,0.9,0.9,0.95,0.95,0.9,0.95]
weighted_recall
0.91 [0.95,0.95,1,0.9,0.95,0.85,0.95,0.85,0.8,0.9]
weighted_recall
0.935 [0.95,0.95,1,0.9,0.95,0.85,1,0.95,0.9,0.9]
weighted_recall
0.88 [1,0.9,0.95,0.85,0.95,0.75,0.9,0.9,0.7,0.9]
weighted_recall
0.9 [1,0.85,1,0.9,0.95,0.95,0.85,0.95,0.75,0.8]
weighted_recall
0.92 [0.95,0.85,0.95,1,0.95,0.9,0.95,0.95,0.8,0.9]
weighted_recall
0.915 [0.95,0.85,0.95,0.9,0.95,0.85,0.95,1,0.8,0.95]
weighted_recall
0.93 [0.95,0.95,1,0.95,0.95,0.9,0.95,0.9,0.85,0.9]
weighted_recall
0.905 [1,0.9,0.95,0.85,0.9,0.95,0.8,0.9,0.85,0.95]