10550987
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)
8275629
add_indicator
false
12737
copy
true
12737
fill_value
null
12737
missing_values
NaN
12737
strategy
"median"
12737
verbose
0
12737
C
500
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
"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.
14
mfeat-fourier
https://www.openml.org/data/download/14/dataset_14_mfeat-fourier.arff
-1
22026929
description
https://api.openml.org/data/download/22026929/description.xml
-1
22026930
predictions
https://api.openml.org/data/download/22026930/predictions.arff
area_under_roc_curve
0.9712877777777779 [0.999967,0.948269,0.992281,0.981033,0.953925,0.977214,0.944231,0.987522,0.995222,0.933214]
average_cost
0
f_measure
0.8018922985854049 [0.995,0.728606,0.910941,0.862944,0.739454,0.852941,0.586207,0.846535,0.94898,0.547315]
kappa
0.7794444444444444
kb_relative_information_score
0.8012365167073758
mean_absolute_error
0.05286918516831766
mean_prior_absolute_error
0.18000000000000554
weighted_recall
0.8015 [0.995,0.745,0.895,0.85,0.745,0.87,0.595,0.855,0.93,0.535]
number_of_instances
2000 [200,200,200,200,200,200,200,200,200,200]
precision
0.802706169041302 [0.995,0.712919,0.927461,0.876289,0.73399,0.836538,0.57767,0.838235,0.96875,0.560209]
predictive_accuracy
0.8015000000000001
prior_entropy
3.3219280948872383
relative_absolute_error
0.2937176953795335
root_mean_prior_squared_error
0.3000000000000046
root_mean_squared_error
0.17155785417678526
root_relative_squared_error
0.5718595139226088
total_cost
0
unweighted_recall
0.8014999999999999 [0.995,0.745,0.895,0.85,0.745,0.87,0.595,0.855,0.93,0.535]
area_under_roc_curve
0.9748055555555556 [1,0.9525,0.998333,0.9875,0.966111,0.998611,0.929722,0.988333,0.999444,0.9275]
area_under_roc_curve
0.9642777777777777 [1,0.918889,0.990556,0.9775,0.926667,0.944722,0.943056,0.990556,0.993889,0.956944]
area_under_roc_curve
0.9669444444444444 [1,0.955556,0.995833,0.944444,0.970833,0.974444,0.899722,0.979722,1,0.948889]
area_under_roc_curve
0.9860555555555557 [1,0.972222,0.990556,0.998611,0.978333,0.976111,0.986389,0.991667,0.993611,0.973056]
area_under_roc_curve
0.9655555555555556 [1,0.916944,0.993333,0.968333,0.962778,0.971111,0.953333,0.987778,0.999444,0.9025]
area_under_roc_curve
0.9685833333333334 [1,0.944722,0.993333,0.976944,0.916667,0.988889,0.956944,0.987778,0.998889,0.921667]
area_under_roc_curve
0.9709444444444444 [1,0.947222,0.978056,0.995,0.966667,0.974167,0.95,0.981389,0.997778,0.919167]
area_under_roc_curve
0.9803333333333335 [1,0.973889,0.996667,0.997778,0.963056,0.986667,0.945556,0.994722,0.993889,0.951111]
area_under_roc_curve
0.9696111111111111 [1,0.921944,0.998333,0.9975,0.9675,0.973333,0.933889,0.992778,1,0.910833]
area_under_roc_curve
0.9736111111111111 [0.999722,0.990278,0.985278,0.989722,0.941944,0.994722,0.936111,0.989167,0.977778,0.931389]
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
0.7905271371038993 [1,0.765957,0.95,0.864865,0.780488,0.904762,0.421053,0.833333,0.952381,0.432432]
f_measure
0.7754711659485222 [1,0.648649,0.842105,0.790698,0.717949,0.857143,0.52381,0.8,0.974359,0.6]
f_measure
0.7709115702103506 [0.974359,0.761905,0.85,0.742857,0.711111,0.8,0.590909,0.864865,0.97561,0.4375]
f_measure
0.8573450210434637 [1,0.789474,0.95,0.888889,0.782609,0.829268,0.789474,0.842105,0.974359,0.727273]
f_measure
0.7696331696576495 [1,0.604651,0.864865,0.809524,0.684211,0.8,0.6,0.818182,0.974359,0.540541]
f_measure
0.7873921435859818 [1,0.717949,0.95,0.857143,0.682927,0.85,0.526316,0.878049,0.95,0.461538]
f_measure
0.8049508242256848 [1,0.717949,0.894737,0.926829,0.790698,0.810811,0.590909,0.883721,0.947368,0.486486]
f_measure
0.8388500166761037 [1,0.8,0.923077,0.952381,0.777778,0.9,0.695652,0.863636,0.864865,0.611111]
f_measure
0.8043294211137599 [1,0.666667,0.926829,0.894737,0.75,0.878049,0.526316,0.829268,1,0.571429]
f_measure
0.8073232673791619 [0.97561,0.8,0.95,0.894737,0.705882,0.9,0.578947,0.85,0.864865,0.553191]
kappa
0.7722222222222223
kappa
0.75
kappa
0.75
kappa
0.8388888888888889
kappa
0.7444444444444445
kappa
0.7666666666666667
kappa
0.7833333333333334
kappa
0.8222222222222222
kappa
0.7833333333333334
kappa
0.7833333333333334
kb_relative_information_score
0.7990476718546735
kb_relative_information_score
0.7990766158361596
kb_relative_information_score
0.7914296367394271
kb_relative_information_score
0.8358183349760744
kb_relative_information_score
0.767276497648365
kb_relative_information_score
0.8042777593553195
kb_relative_information_score
0.7887341109863623
kb_relative_information_score
0.8156481036031795
kb_relative_information_score
0.8081264695330281
kb_relative_information_score
0.8029299665408937
mean_absolute_error
0.054156774550375146
mean_absolute_error
0.05406596340340707
mean_absolute_error
0.0556330750563082
mean_absolute_error
0.048099090491046194
mean_absolute_error
0.0569716048610346
mean_absolute_error
0.05142341491021361
mean_absolute_error
0.053930735999684225
mean_absolute_error
0.049292433841950416
mean_absolute_error
0.053295226056521754
mean_absolute_error
0.05182353251263517
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
0.7945007851625498 [1,0.666667,0.95,0.941176,0.761905,0.863636,0.444444,0.9375,0.909091,0.470588]
precision
0.7788925600057649 [1,0.705882,0.888889,0.73913,0.736842,0.818182,0.5,0.8,1,0.6]
precision
0.782249681690858 [1,0.727273,0.85,0.866667,0.64,0.72,0.541667,0.941176,0.952381,0.583333]
precision
0.8674053724053725 [1,0.833333,0.95,1,0.692308,0.809524,0.833333,0.888889,1,0.666667]
precision
0.7739578650959725 [1,0.565217,0.941176,0.772727,0.722222,0.8,0.6,0.75,1,0.588235]
precision
0.7858073213336371 [1,0.736842,0.95,0.818182,0.666667,0.85,0.555556,0.857143,0.95,0.473684]
precision
0.8104697218322873 [1,0.736842,0.944444,0.904762,0.73913,0.882353,0.541667,0.826087,1,0.529412]
precision
0.8467187082783058 [1,0.8,0.947368,0.909091,0.875,0.9,0.615385,0.791667,0.941176,0.6875]
precision
0.8051093643198907 [1,0.684211,0.904762,0.944444,0.75,0.857143,0.555556,0.809524,1,0.545455]
precision
0.8207737317149081 [0.952381,0.72,0.95,0.944444,0.857143,0.9,0.611111,0.85,0.941176,0.481481]
predictive_accuracy
0.795
predictive_accuracy
0.775
predictive_accuracy
0.775
predictive_accuracy
0.855
predictive_accuracy
0.77
predictive_accuracy
0.79
predictive_accuracy
0.805
predictive_accuracy
0.84
predictive_accuracy
0.805
predictive_accuracy
0.805
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
0.3008709697243067
relative_absolute_error
0.30036646335226186
relative_absolute_error
0.3090726392017126
relative_absolute_error
0.26721716939470136
relative_absolute_error
0.31650891589463703
relative_absolute_error
0.28568563839007594
relative_absolute_error
0.29961519999824604
relative_absolute_error
0.27384685467750264
relative_absolute_error
0.29608458920289893
relative_absolute_error
0.28790851395908457
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
0.1712367038395079
root_mean_squared_error
0.17486511840993355
root_mean_squared_error
0.17717354557537865
root_mean_squared_error
0.15352212727502895
root_mean_squared_error
0.1887577706318059
root_mean_squared_error
0.17262233914498276
root_mean_squared_error
0.17944989568547384
root_mean_squared_error
0.16163344446509192
root_mean_squared_error
0.16538157775707804
root_mean_squared_error
0.16838935971704952
root_relative_squared_error
0.5707890127983599
root_relative_squared_error
0.5828837280331122
root_relative_squared_error
0.5905784852512624
root_relative_squared_error
0.5117404242500968
root_relative_squared_error
0.6291925687726867
root_relative_squared_error
0.5754077971499428
root_relative_squared_error
0.5981663189515798
root_relative_squared_error
0.5387781482169735
root_relative_squared_error
0.5512719258569272
root_relative_squared_error
0.5612978657234987
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
0.795 [1,0.9,0.95,0.8,0.8,0.95,0.4,0.75,1,0.4]
unweighted_recall
0.775 [1,0.6,0.8,0.85,0.7,0.9,0.55,0.8,0.95,0.6]
unweighted_recall
0.775 [0.95,0.8,0.85,0.65,0.8,0.9,0.65,0.8,1,0.35]
unweighted_recall
0.8550000000000001 [1,0.75,0.95,0.8,0.9,0.85,0.75,0.8,0.95,0.8]
unweighted_recall
0.77 [1,0.65,0.8,0.85,0.65,0.8,0.6,0.9,0.95,0.5]
unweighted_recall
0.79 [1,0.7,0.95,0.9,0.7,0.85,0.5,0.9,0.95,0.45]
unweighted_recall
0.805 [1,0.7,0.85,0.95,0.85,0.75,0.65,0.95,0.9,0.45]
unweighted_recall
0.8400000000000001 [1,0.8,0.9,1,0.7,0.9,0.8,0.95,0.8,0.55]
unweighted_recall
0.8049999999999999 [1,0.65,0.95,0.85,0.75,0.9,0.5,0.85,1,0.6]
unweighted_recall
0.8049999999999999 [1,0.9,0.95,0.85,0.6,0.9,0.55,0.85,0.8,0.65]
usercpu_time_millis
354.55650702351704
usercpu_time_millis
346.68544598389417
usercpu_time_millis
331.22498396551237
usercpu_time_millis
321.8503989628516
usercpu_time_millis
310.4716599918902
usercpu_time_millis
340.61680699232966
usercpu_time_millis
334.1672259848565
usercpu_time_millis
333.2100959960371
usercpu_time_millis
336.33956901030615
usercpu_time_millis
340.2048220159486
usercpu_time_millis_testing
0.7493619923479855
usercpu_time_millis_testing
0.7975450134836137
usercpu_time_millis_testing
0.7395719876512885
usercpu_time_millis_testing
0.7220389670692384
usercpu_time_millis_testing
0.7852989947423339
usercpu_time_millis_testing
0.7320049917325377
usercpu_time_millis_testing
0.8169270004145801
usercpu_time_millis_testing
0.7543590036220849
usercpu_time_millis_testing
0.8084489963948727
usercpu_time_millis_testing
0.7827520021237433
usercpu_time_millis_training
353.80714503116906
usercpu_time_millis_training
345.88790097041056
usercpu_time_millis_training
330.4854119778611
usercpu_time_millis_training
321.1283599957824
usercpu_time_millis_training
309.68636099714786
usercpu_time_millis_training
339.8848020005971
usercpu_time_millis_training
333.3502989844419
usercpu_time_millis_training
332.45573699241504
usercpu_time_millis_training
335.5311200139113
usercpu_time_millis_training
339.42207001382485
wall_clock_time_millis
354.56371307373047
wall_clock_time_millis
346.6906547546387
wall_clock_time_millis
331.24399185180664
wall_clock_time_millis
321.87938690185547
wall_clock_time_millis
310.5027675628662
wall_clock_time_millis
340.620756149292
wall_clock_time_millis
334.1715335845947
wall_clock_time_millis
333.21523666381836
wall_clock_time_millis
336.46488189697266
wall_clock_time_millis
342.06080436706543
wall_clock_time_millis_testing
0.7526874542236328
wall_clock_time_millis_testing
0.8003711700439453
wall_clock_time_millis_testing
0.7424354553222656
wall_clock_time_millis_testing
0.7250308990478516
wall_clock_time_millis_testing
0.7877349853515625
wall_clock_time_millis_testing
0.7345676422119141
wall_clock_time_millis_testing
0.8203983306884766
wall_clock_time_millis_testing
0.7569789886474609
wall_clock_time_millis_testing
0.8111000061035156
wall_clock_time_millis_testing
0.7855892181396484
wall_clock_time_millis_training
353.81102561950684
wall_clock_time_millis_training
345.8902835845947
wall_clock_time_millis_training
330.5015563964844
wall_clock_time_millis_training
321.1543560028076
wall_clock_time_millis_training
309.71503257751465
wall_clock_time_millis_training
339.8861885070801
wall_clock_time_millis_training
333.35113525390625
wall_clock_time_millis_training
332.4582576751709
wall_clock_time_millis_training
335.65378189086914
wall_clock_time_millis_training
341.2752151489258
weighted_recall
0.795 [1,0.9,0.95,0.8,0.8,0.95,0.4,0.75,1,0.4]
weighted_recall
0.775 [1,0.6,0.8,0.85,0.7,0.9,0.55,0.8,0.95,0.6]
weighted_recall
0.775 [0.95,0.8,0.85,0.65,0.8,0.9,0.65,0.8,1,0.35]
weighted_recall
0.855 [1,0.75,0.95,0.8,0.9,0.85,0.75,0.8,0.95,0.8]
weighted_recall
0.77 [1,0.65,0.8,0.85,0.65,0.8,0.6,0.9,0.95,0.5]
weighted_recall
0.79 [1,0.7,0.95,0.9,0.7,0.85,0.5,0.9,0.95,0.45]
weighted_recall
0.805 [1,0.7,0.85,0.95,0.85,0.75,0.65,0.95,0.9,0.45]
weighted_recall
0.84 [1,0.8,0.9,1,0.7,0.9,0.8,0.95,0.8,0.55]
weighted_recall
0.805 [1,0.65,0.95,0.85,0.75,0.9,0.5,0.85,1,0.6]
weighted_recall
0.805 [1,0.9,0.95,0.85,0.6,0.9,0.55,0.85,0.8,0.65]