10228498
6138
Felix Neutatz
10101
Supervised Classification
12647
sklearn.pipeline.C58b630419e517(n3=sklearn.compose._column_transformer.C3771de2902eab9(n4=sklearn.preprocessing._function_transformer.C3771de2902e830),n5=fastsklearnfeature.transformations.mdlp_discretization.MDLPDiscretizerTransformation.C58b630419e4b0,c=sklearn.linear_model.logistic.LogisticRegression)(1)
8153726
C
0.001
9801
class_weight
"balanced"
9801
dual
false
9801
fit_intercept
true
9801
intercept_scaling
1
9801
max_iter
10000
9801
multi_class
"auto"
9801
n_jobs
null
9801
penalty
"l2"
9801
random_state
26840
9801
solver
"lbfgs"
9801
tol
0.0001
9801
verbose
0
9801
warm_start
false
9801
memory
null
12647
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "n3", "step_name": "n3"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "n5", "step_name": "n5"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "c", "step_name": "c"}}]
12647
n_jobs
null
12648
remainder
"drop"
12648
sparse_threshold
0.3
12648
transformer_weights
null
12648
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "n4", "step_name": "n4", "argument_1": [0]}}]
12648
accept_sparse
false
12649
check_inverse
true
12649
func
{"oml-python:serialized_object": "function", "value": "fastsklearnfeature.candidates.Identity.identity"}
12649
inv_kw_args
null
12649
inverse_func
null
12649
kw_args
null
12649
pass_y
"deprecated"
12649
validate
false
12649
ComplexityDriven
openml-python
Sklearn_0.20.3.
1464
blood-transfusion-service-center
https://www.openml.org/data/download/1586225/php0iVrYT
-1
21378291
description
https://api.openml.org/data/download/21378291/description.xml
-1
21378292
predictions
https://api.openml.org/data/download/21378292/predictions.arff
area_under_roc_curve
0.6594322885866352 [0.659432,0.659432]
average_cost
0
f_measure
0.6645199013032912 [0.715037,0.502752]
kappa
0.2682233004100965
kb_relative_information_score
-0.6963427817907131
mean_absolute_error
0.4973030419617903
mean_prior_absolute_error
0.3630445632798566
number_of_instances
748 [570,178]
precision
0.7688613419891019 [0.892388,0.373297]
predictive_accuracy
0.6377005347593583
prior_entropy
0.7916465694609683
recall
0.6377005347593583 [0.596491,0.769663]
relative_absolute_error
1.3698126683650105
root_mean_prior_squared_error
0.4258399633559147
root_mean_squared_error
0.49735288050335863
root_relative_squared_error
1.1679337856970315
total_cost
0
area_under_roc_curve
0.695906432748538 [0.695906,0.695906]
area_under_roc_curve
0.7602339181286549 [0.760234,0.760234]
area_under_roc_curve
0.6783625730994152 [0.678363,0.678363]
area_under_roc_curve
0.6403508771929824 [0.640351,0.640351]
area_under_roc_curve
0.7046783625730996 [0.704678,0.704678]
area_under_roc_curve
0.6505847953216374 [0.650585,0.650585]
area_under_roc_curve
0.6505847953216374 [0.650585,0.650585]
area_under_roc_curve
0.6345029239766082 [0.634503,0.634503]
area_under_roc_curve
0.6599587203302374 [0.659959,0.659959]
area_under_roc_curve
0.7569659442724459 [0.756966,0.756966]
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
0.6786111111111113 [0.729167,0.518519]
f_measure
0.7156363636363636 [0.757895,0.581818]
f_measure
0.6536170212765957 [0.702128,0.5]
f_measure
0.6536263736263735 [0.714286,0.461538]
f_measure
0.6909161641703948 [0.742268,0.528302]
f_measure
0.6414545454545455 [0.694737,0.472727]
f_measure
0.6414545454545455 [0.694737,0.472727]
f_measure
0.5883661816172409 [0.629213,0.459016]
f_measure
0.6639732516021175 [0.721649,0.470588]
f_measure
0.7138194798572156 [0.757895,0.566038]
kappa
0.2919389978213508
kappa
0.38238453276047274
kappa
0.2584745762711865
kappa
0.21524663677130054
kappa
0.3093922651933701
kappa
0.2212674543501611
kappa
0.2212674543501611
kappa
0.18235877106045603
kappa
0.23682200152788377
kappa
0.369162342475908
kb_relative_information_score
-0.6871154608034833
kb_relative_information_score
-0.6856385640110156
kb_relative_information_score
-0.6884946904606654
kb_relative_information_score
-0.688033381268117
kb_relative_information_score
-0.6864376507994531
kb_relative_information_score
-0.6889752391456925
kb_relative_information_score
-0.6889752391456925
kb_relative_information_score
-0.6920804416705721
kb_relative_information_score
-0.7310170748783807
kb_relative_information_score
-0.728993803123842
mean_absolute_error
0.4970839436816729
mean_absolute_error
0.4966751680039134
mean_absolute_error
0.49746352793925497
mean_absolute_error
0.4973387503662751
mean_absolute_error
0.49689740513413044
mean_absolute_error
0.49759683369543256
mean_absolute_error
0.49759683369543256
mean_absolute_error
0.4984504468582053
mean_absolute_error
0.4972333113849837
mean_absolute_error
0.4966850289440197
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.36410666666666686
mean_prior_absolute_error
0.35873873873873896
mean_prior_absolute_error
0.35873873873873896
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
75 [57,18]
number_of_instances
74 [57,17]
number_of_instances
74 [57,17]
precision
0.7753846153846153 [0.897436,0.388889]
precision
0.8237837837837838 [0.947368,0.432432]
precision
0.7662588904694168 [0.891892,0.368421]
precision
0.7334863701578191 [0.853659,0.352941]
precision
0.7800000000000001 [0.9,0.4]
precision
0.7443243243243243 [0.868421,0.351351]
precision
0.7443243243243243 [0.868421,0.351351]
precision
0.743139534883721 [0.875,0.325581]
precision
0.7550675675675675 [0.875,0.352941]
precision
0.8254504504504505 [0.947368,0.416667]
predictive_accuracy
0.6533333333333333
predictive_accuracy
0.6933333333333332
predictive_accuracy
0.6266666666666666
predictive_accuracy
0.6266666666666666
predictive_accuracy
0.6666666666666667
predictive_accuracy
0.6133333333333334
predictive_accuracy
0.6133333333333334
predictive_accuracy
0.56
predictive_accuracy
0.6351351351351352
predictive_accuracy
0.6891891891891891
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7950473279640615
prior_entropy
0.7778597106646706
prior_entropy
0.7778597106646706
recall
0.6533333333333333 [0.614035,0.777778]
recall
0.6933333333333334 [0.631579,0.888889]
recall
0.6266666666666667 [0.578947,0.777778]
recall
0.6266666666666667 [0.614035,0.666667]
recall
0.6666666666666666 [0.631579,0.777778]
recall
0.6133333333333333 [0.578947,0.722222]
recall
0.6133333333333333 [0.578947,0.722222]
recall
0.56 [0.491228,0.777778]
recall
0.6351351351351351 [0.614035,0.705882]
recall
0.6891891891891891 [0.631579,0.882353]
relative_absolute_error
1.3652151668421508
relative_absolute_error
1.364092485729218
relative_absolute_error
1.3662576752396405
relative_absolute_error
1.3659149801329504
relative_absolute_error
1.3647028484348822
relative_absolute_error
1.3666237925573979
relative_absolute_error
1.3666237925573979
relative_absolute_error
1.3689681966590512
relative_absolute_error
1.3860597077783317
relative_absolute_error
1.3845313463783566
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4270852113779844
root_mean_prior_squared_error
0.4207539065176338
root_mean_prior_squared_error
0.4207539065176338
root_mean_squared_error
0.49713198760540267
root_mean_squared_error
0.49671559632130713
root_mean_squared_error
0.49751373265662735
root_mean_squared_error
0.49739365325686824
root_mean_squared_error
0.4969442836353563
root_mean_squared_error
0.49765029464699256
root_mean_squared_error
0.4976502946469925
root_mean_squared_error
0.49850496054585125
root_mean_squared_error
0.49728581791374316
root_mean_squared_error
0.49672637739358205
root_relative_squared_error
1.1640112426309808
root_relative_squared_error
1.1630362819603641
root_relative_squared_error
1.1649050807716015
root_relative_squared_error
1.164623920486581
root_relative_squared_error
1.163571742584981
root_relative_squared_error
1.1652248342697957
root_relative_squared_error
1.1652248342697957
root_relative_squared_error
1.1672259944038614
root_relative_squared_error
1.18189233708969
root_relative_squared_error
1.180562722529979
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
46.76372400000028
usercpu_time_millis
16.190558999999993
usercpu_time_millis
10.490588999999773
usercpu_time_millis
7.98664899999979
usercpu_time_millis
7.59162499999988
usercpu_time_millis
8.60897699999974
usercpu_time_millis
9.195897999999758
usercpu_time_millis
9.338282999999947
usercpu_time_millis
9.531466000000322
usercpu_time_millis
9.364413999999766
usercpu_time_millis_testing
2.1209560000001737
usercpu_time_millis_testing
0.8397369999997295
usercpu_time_millis_testing
0.6041039999997722
usercpu_time_millis_testing
0.5325809999998654
usercpu_time_millis_testing
0.5866389999997779
usercpu_time_millis_testing
0.6138499999996938
usercpu_time_millis_testing
0.5941989999995734
usercpu_time_millis_testing
0.5873020000000118
usercpu_time_millis_testing
0.6212400000000784
usercpu_time_millis_testing
0.6068780000001439
usercpu_time_millis_training
44.64276800000011
usercpu_time_millis_training
15.350822000000264
usercpu_time_millis_training
9.886485
usercpu_time_millis_training
7.454067999999925
usercpu_time_millis_training
7.004986000000102
usercpu_time_millis_training
7.995127000000046
usercpu_time_millis_training
8.601699000000185
usercpu_time_millis_training
8.750980999999936
usercpu_time_millis_training
8.910226000000243
usercpu_time_millis_training
8.757535999999622