10557692
8323
Heinrich Peters
14
Supervised Classification
18591
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression)(1)
8275574
copy
true
17405
with_mean
true
17405
with_std
true
17405
add_indicator
false
17407
copy
true
17407
fill_value
null
17407
missing_values
NaN
17407
strategy
"median"
17407
verbose
0
17407
C
0.001
17462
class_weight
null
17462
dual
false
17462
fit_intercept
true
17462
intercept_scaling
1
17462
l1_ratio
null
17462
max_iter
10000
17462
multi_class
"warn"
17462
n_jobs
null
17462
penalty
"l2"
17462
random_state
1
17462
solver
"lbfgs"
17462
tol
0.0001
17462
verbose
0
17462
warm_start
false
17462
memory
null
18591
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"}}]
18591
verbose
false
18591
openml-python
Sklearn_0.21.2.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
22040344
description
https://api.openml.org/data/download/22040344/description.xml
-1
22040345
predictions
https://api.openml.org/data/download/22040345/predictions.arff
area_under_roc_curve
0.9551936111111111 [0.999756,0.916325,0.988911,0.979239,0.918992,0.987464,0.903592,0.981203,0.979831,0.896625]
average_cost
0
f_measure
0.7563822809066966 [0.982278,0.704301,0.913151,0.836735,0.685237,0.839002,0.484375,0.783599,0.874439,0.460705]
kappa
0.7366666666666667
kb_relative_information_score
0.41425616059560866
mean_absolute_error
0.1434100551188661
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.763 [0.97,0.655,0.92,0.82,0.615,0.925,0.465,0.86,0.975,0.425]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.7579031631120215 [0.994872,0.761628,0.906404,0.854167,0.773585,0.767635,0.505435,0.719665,0.792683,0.502959]
predictive_accuracy
0.763
prior_entropy
3.3219280948872383
relative_absolute_error
0.7967225284381203
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.24630010740918373
root_relative_squared_error
0.8210003580305998
total_cost
0
unweighted_recall
0.7629999999999999 [0.97,0.655,0.92,0.82,0.615,0.925,0.465,0.86,0.975,0.425]
area_under_roc_curve
0.9580833333333334 [0.9975,0.916111,0.993889,0.984444,0.939444,0.997222,0.835278,0.981111,0.995556,0.940278]
area_under_roc_curve
0.9536666666666668 [1,0.911389,0.976667,0.990833,0.883611,0.992222,0.932222,0.980833,0.966111,0.902778]
area_under_roc_curve
0.950388888888889 [1,0.914444,0.991944,0.958056,0.915556,0.991944,0.905,0.960833,0.998889,0.867222]
area_under_roc_curve
0.9571111111111111 [0.999722,0.893056,0.998889,0.9925,0.978056,0.990556,0.905,0.964444,0.948056,0.900833]
area_under_roc_curve
0.9526666666666667 [1,0.866389,0.985833,0.961944,0.915278,0.988333,0.903889,0.986944,1,0.918056]
area_under_roc_curve
0.9592222222222223 [1,0.915,0.995833,0.973611,0.919444,0.981389,0.924444,0.991389,1,0.891111]
area_under_roc_curve
0.9597222222222221 [1,0.921111,0.994722,0.985,0.904167,0.965278,0.96,0.992222,0.996667,0.878056]
area_under_roc_curve
0.9649722222222222 [1,0.948333,0.989444,0.995,0.8875,0.994444,0.917222,0.986944,0.993333,0.9375]
area_under_roc_curve
0.9609722222222223 [1,0.909444,0.999167,0.987222,0.943333,0.975556,0.918333,0.989444,0.998889,0.888333]
area_under_roc_curve
0.9421666666666666 [1,0.974444,0.961667,0.963611,0.915278,0.994444,0.860556,0.985556,0.909444,0.856667]
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
0.713862173647613 [0.947368,0.736842,0.809524,0.8,0.833333,0.904762,0.243902,0.682927,0.816327,0.363636]
f_measure
0.7689511030974445 [1,0.628571,0.926829,0.871795,0.666667,0.844444,0.615385,0.727273,0.844444,0.564103]
f_measure
0.7648332343783593 [0.947368,0.684211,0.923077,0.761905,0.736842,0.8,0.540541,0.829268,0.869565,0.555556]
f_measure
0.7683789855155684 [0.974359,0.588235,0.974359,0.857143,0.7,0.863636,0.611111,0.744186,0.844444,0.526316]
f_measure
0.7352998954188987 [1,0.594595,0.894737,0.829268,0.611111,0.75,0.55,0.755556,0.930233,0.4375]
f_measure
0.7551286831721614 [1,0.777778,0.952381,0.8,0.648649,0.826087,0.342857,0.844444,0.909091,0.45]
f_measure
0.7672198200689314 [1,0.702703,0.947368,0.878049,0.666667,0.818182,0.619048,0.808511,0.909091,0.322581]
f_measure
0.7687470590233297 [0.95,0.769231,0.926829,0.820513,0.625,0.857143,0.55814,0.782609,0.883721,0.514286]
f_measure
0.782270473171636 [1,0.769231,0.952381,0.864865,0.611111,0.818182,0.4375,0.883721,0.952381,0.533333]
f_measure
0.7337493942371991 [1,0.769231,0.829268,0.888889,0.742857,0.926829,0.307692,0.772727,0.8,0.3]
kappa
0.6888888888888889
kappa
0.75
kappa
0.7444444444444445
kappa
0.75
kappa
0.7166666666666667
kappa
0.7388888888888889
kappa
0.7555555555555555
kappa
0.75
kappa
0.7666666666666667
kappa
0.7055555555555556
kb_relative_information_score
0.4065724111322051
kb_relative_information_score
0.4216319465804031
kb_relative_information_score
0.40352807525430145
kb_relative_information_score
0.4144503080784711
kb_relative_information_score
0.4101194397007455
kb_relative_information_score
0.4208296628710604
kb_relative_information_score
0.4217306103207285
kb_relative_information_score
0.42781441965902445
kb_relative_information_score
0.41284486250973473
kb_relative_information_score
0.40303986984926593
mean_absolute_error
0.144281107142696
mean_absolute_error
0.1423560831915366
mean_absolute_error
0.14499988440908987
mean_absolute_error
0.14368046717330943
mean_absolute_error
0.14340496074077405
mean_absolute_error
0.14228711231332158
mean_absolute_error
0.14256157612159773
mean_absolute_error
0.14245125498937192
mean_absolute_error
0.14383620182420845
mean_absolute_error
0.14424190328275358
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
0.7207596952855573 [1,0.777778,0.772727,0.8,0.9375,0.863636,0.238095,0.666667,0.689655,0.461538]
precision
0.7776178908810486 [1,0.733333,0.904762,0.894737,0.846154,0.76,0.631579,0.666667,0.76,0.578947]
precision
0.7686631021197584 [1,0.722222,0.947368,0.727273,0.777778,0.72,0.588235,0.809524,0.769231,0.625]
precision
0.7722841928602797 [1,0.714286,1,0.818182,0.7,0.791667,0.6875,0.695652,0.76,0.555556]
precision
0.7414282771079447 [1,0.647059,0.944444,0.809524,0.6875,0.642857,0.55,0.68,0.869565,0.583333]
precision
0.7597409159467984 [1,0.875,0.909091,0.933333,0.705882,0.730769,0.4,0.76,0.833333,0.45]
precision
0.770434032198738 [1,0.764706,1,0.857143,0.75,0.75,0.590909,0.703704,0.833333,0.454545]
precision
0.7777989782909691 [0.95,0.789474,0.904762,0.842105,0.833333,0.818182,0.521739,0.692308,0.826087,0.6]
precision
0.7875752262835652 [1,0.789474,0.909091,0.941176,0.6875,0.75,0.583333,0.826087,0.909091,0.48]
precision
0.7414548872180453 [1,0.789474,0.809524,1,0.866667,0.904762,0.315789,0.708333,0.72,0.3]
predictive_accuracy
0.72
predictive_accuracy
0.775
predictive_accuracy
0.77
predictive_accuracy
0.775
predictive_accuracy
0.745
predictive_accuracy
0.765
predictive_accuracy
0.78
predictive_accuracy
0.775
predictive_accuracy
0.79
predictive_accuracy
0.735
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
0.8015617063483121
relative_absolute_error
0.7908671288418708
relative_absolute_error
0.8055549133838334
relative_absolute_error
0.7982248176294978
relative_absolute_error
0.7966942263376344
relative_absolute_error
0.790483957296232
relative_absolute_error
0.7920087562310993
relative_absolute_error
0.791395861052067
relative_absolute_error
0.7990900101344923
relative_absolute_error
0.8013439071264097
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
0.24777312976266636
root_mean_squared_error
0.2451260038098247
root_mean_squared_error
0.2485875370483592
root_mean_squared_error
0.24653715503077084
root_mean_squared_error
0.2466068121389143
root_mean_squared_error
0.24449583312406842
root_mean_squared_error
0.24476119386634246
root_mean_squared_error
0.2442668004566804
root_mean_squared_error
0.24672786917675546
root_mean_squared_error
0.24807404070173142
root_relative_squared_error
0.8259104325422217
root_relative_squared_error
0.8170866793660828
root_relative_squared_error
0.8286251234945311
root_relative_squared_error
0.8217905167692366
root_relative_squared_error
0.8220227071297148
root_relative_squared_error
0.8149861104135618
root_relative_squared_error
0.815870646221142
root_relative_squared_error
0.8142226681889352
root_relative_squared_error
0.8224262305891853
root_relative_squared_error
0.8269134690057719
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
0.72 [0.9,0.7,0.85,0.8,0.75,0.95,0.25,0.7,1,0.3]
unweighted_recall
0.775 [1,0.55,0.95,0.85,0.55,0.95,0.6,0.8,0.95,0.55]
unweighted_recall
0.77 [0.9,0.65,0.9,0.8,0.7,0.9,0.5,0.85,1,0.5]
unweighted_recall
0.775 [0.95,0.5,0.95,0.9,0.7,0.95,0.55,0.8,0.95,0.5]
unweighted_recall
0.7449999999999999 [1,0.55,0.85,0.85,0.55,0.9,0.55,0.85,1,0.35]
unweighted_recall
0.765 [1,0.7,1,0.7,0.6,0.95,0.3,0.95,1,0.45]
unweighted_recall
0.78 [1,0.65,0.9,0.9,0.6,0.9,0.65,0.95,1,0.25]
unweighted_recall
0.7750000000000001 [0.95,0.75,0.95,0.8,0.5,0.9,0.6,0.9,0.95,0.45]
unweighted_recall
0.7899999999999999 [1,0.75,1,0.8,0.55,0.9,0.35,0.95,1,0.6]
unweighted_recall
0.7350000000000001 [1,0.75,0.85,0.8,0.65,0.95,0.3,0.85,0.9,0.3]
usercpu_time_millis
151.36800000027506
usercpu_time_millis
179.13799999996627
usercpu_time_millis
178.00800000031813
usercpu_time_millis
182.69400000008318
usercpu_time_millis
186.97800000018105
usercpu_time_millis
182.09999999953652
usercpu_time_millis
182.35199999980978
usercpu_time_millis
178.2100000000355
usercpu_time_millis
177.80000000038854
usercpu_time_millis
187.54200000012133
usercpu_time_millis_testing
1.9339999998919666
usercpu_time_millis_testing
1.9240000001445878
usercpu_time_millis_testing
1.8939999999929569
usercpu_time_millis_testing
1.9280000001344888
usercpu_time_millis_testing
1.9999999999527063
usercpu_time_millis_testing
1.9279999996797414
usercpu_time_millis_testing
2.1659999997609702
usercpu_time_millis_testing
1.9280000001344888
usercpu_time_millis_testing
2.0060000001649314
usercpu_time_millis_testing
1.7920000000231084
usercpu_time_millis_training
149.4340000003831
usercpu_time_millis_training
177.21399999982168
usercpu_time_millis_training
176.11400000032518
usercpu_time_millis_training
180.7659999999487
usercpu_time_millis_training
184.97800000022835
usercpu_time_millis_training
180.17199999985678
usercpu_time_millis_training
180.1860000000488
usercpu_time_millis_training
176.28199999990102
usercpu_time_millis_training
175.7940000002236
usercpu_time_millis_training
185.75000000009823
wall_clock_time_millis
44.16394233703613
wall_clock_time_millis
45.22442817687988
wall_clock_time_millis
44.80385780334473
wall_clock_time_millis
46.16880416870117
wall_clock_time_millis
53.69710922241211
wall_clock_time_millis
46.03981971740723
wall_clock_time_millis
46.98300361633301
wall_clock_time_millis
45.11594772338867
wall_clock_time_millis
44.81792449951172
wall_clock_time_millis
47.605037689208984
wall_clock_time_millis_testing
0.5202293395996094
wall_clock_time_millis_testing
0.5152225494384766
wall_clock_time_millis_testing
0.5121231079101562
wall_clock_time_millis_testing
0.5168914794921875
wall_clock_time_millis_testing
0.5369186401367188
wall_clock_time_millis_testing
0.5156993865966797
wall_clock_time_millis_testing
0.5710124969482422
wall_clock_time_millis_testing
0.5152225494384766
wall_clock_time_millis_testing
0.537872314453125
wall_clock_time_millis_testing
0.47898292541503906
wall_clock_time_millis_training
43.64371299743652
wall_clock_time_millis_training
44.709205627441406
wall_clock_time_millis_training
44.29173469543457
wall_clock_time_millis_training
45.651912689208984
wall_clock_time_millis_training
53.16019058227539
wall_clock_time_millis_training
45.52412033081055
wall_clock_time_millis_training
46.411991119384766
wall_clock_time_millis_training
44.600725173950195
wall_clock_time_millis_training
44.280052185058594
wall_clock_time_millis_training
47.126054763793945
weighted_recall
0.72 [0.9,0.7,0.85,0.8,0.75,0.95,0.25,0.7,1,0.3]
weighted_recall
0.775 [1,0.55,0.95,0.85,0.55,0.95,0.6,0.8,0.95,0.55]
weighted_recall
0.77 [0.9,0.65,0.9,0.8,0.7,0.9,0.5,0.85,1,0.5]
weighted_recall
0.775 [0.95,0.5,0.95,0.9,0.7,0.95,0.55,0.8,0.95,0.5]
weighted_recall
0.745 [1,0.55,0.85,0.85,0.55,0.9,0.55,0.85,1,0.35]
weighted_recall
0.765 [1,0.7,1,0.7,0.6,0.95,0.3,0.95,1,0.45]
weighted_recall
0.78 [1,0.65,0.9,0.9,0.6,0.9,0.65,0.95,1,0.25]
weighted_recall
0.775 [0.95,0.75,0.95,0.8,0.5,0.9,0.6,0.9,0.95,0.45]
weighted_recall
0.79 [1,0.75,1,0.8,0.55,0.9,0.35,0.95,1,0.6]
weighted_recall
0.735 [1,0.75,0.85,0.8,0.65,0.95,0.3,0.85,0.9,0.3]