10553056
8323
Heinrich Peters
219
Supervised Classification
18607
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),logisticregression=sklearn.linear_model.logistic.LogisticRegression)(2)
8275727
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
"most_frequent"
17407
verbose
0
17407
categorical_features
null
17408
categories
null
17408
drop
null
17408
dtype
{"oml-python:serialized_object": "type", "value": "np.float64"}
17408
handle_unknown
"ignore"
17408
n_values
null
17408
sparse
true
17408
C
0.01
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
n_jobs
null
18299
remainder
"drop"
18299
sparse_threshold
0.3
18299
transformer_weights
null
18299
transformers
[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [true, false, true, true, true, true, true, true]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, true, false, false, false, false, false, false]}}]
18299
verbose
false
18299
memory
null
18300
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
18300
verbose
false
18300
memory
null
18301
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
18301
verbose
false
18301
memory
null
18607
steps
[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "logisticregression", "step_name": "logisticregression"}}]
18607
verbose
false
18607
openml-python
Sklearn_0.21.2.
151
electricity
https://www.openml.org/data/download/2419/electricity-normalized.arff
-1
22031067
description
https://api.openml.org/data/download/22031067/description.xml
-1
22031068
predictions
https://api.openml.org/data/download/22031068/predictions.arff
area_under_roc_curve
0.827138065023404 [0.827138,0.827138]
average_cost
0
f_measure
0.7545609755249156 [0.68505,0.805843]
kappa
0.49488465416896854
kb_relative_information_score
0.3430868167991273
mean_absolute_error
0.3350687016352604
mean_prior_absolute_error
0.4886137014923867
weighted_recall
0.7597766596045198 [0.615377,0.866309]
number_of_instances
45312 [19237,26075]
precision
0.7614386595610024 [0.772514,0.753268]
predictive_accuracy
0.7597766596045197
prior_entropy
0.9835093906388539
relative_absolute_error
0.6857537981678585
root_mean_prior_squared_error
0.4942738102212943
root_mean_squared_error
0.40579655796656755
root_relative_squared_error
0.820995467643503
total_cost
0
unweighted_recall
0.7408426714039953 [0.615377,0.866309]
area_under_roc_curve
0.8280787645243167 [0.828079,0.828079]
area_under_roc_curve
0.8236389631136564 [0.823639,0.823639]
area_under_roc_curve
0.8134891109574653 [0.813489,0.813489]
area_under_roc_curve
0.828239698492863 [0.82824,0.82824]
area_under_roc_curve
0.828185271223246 [0.828185,0.828185]
area_under_roc_curve
0.8220329960836289 [0.822033,0.822033]
area_under_roc_curve
0.8414154838205471 [0.841415,0.841415]
area_under_roc_curve
0.8343520397257608 [0.834352,0.834352]
area_under_roc_curve
0.8205322077913791 [0.820532,0.820532]
area_under_roc_curve
0.8320657826313053 [0.832066,0.832066]
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
0.7552871974795298 [0.685598,0.806699]
f_measure
0.7567298100502943 [0.688581,0.807005]
f_measure
0.7430202693435545 [0.668994,0.797653]
f_measure
0.7559351655405061 [0.689891,0.804676]
f_measure
0.7493144193580151 [0.675454,0.803824]
f_measure
0.7545946331331403 [0.684103,0.806618]
f_measure
0.769243883619886 [0.70699,0.815188]
f_measure
0.7607132262224116 [0.692731,0.81084]
f_measure
0.746169882792694 [0.672875,0.800213]
f_measure
0.754398400901231 [0.684622,0.805848]
kappa
0.49639472857330713
kappa
0.49931176030600083
kappa
0.47124349318980696
kappa
0.49765635320514146
kappa
0.4843157601285383
kappa
0.4950460617475015
kappa
0.5250469330491239
kappa
0.5074981331630257
kappa
0.4776312018706977
kappa
0.494500911418035
kb_relative_information_score
0.34190198152774715
kb_relative_information_score
0.33983018473966425
kb_relative_information_score
0.32528548000281726
kb_relative_information_score
0.34567194398022677
kb_relative_information_score
0.3449437465323923
kb_relative_information_score
0.3393152334114331
kb_relative_information_score
0.3579621861848189
kb_relative_information_score
0.35209033979684146
kb_relative_information_score
0.334908523573287
kb_relative_information_score
0.34896000229563434
mean_absolute_error
0.33591961766014306
mean_absolute_error
0.33670535623611747
mean_absolute_error
0.34279653313348013
mean_absolute_error
0.3337405667452999
mean_absolute_error
0.33385117921098717
mean_absolute_error
0.3368977742718766
mean_absolute_error
0.3289761775924046
mean_absolute_error
0.3311830370107735
mean_absolute_error
0.3384796509121684
mean_absolute_error
0.33213657456796447
mean_prior_absolute_error
0.48861238171727794
mean_prior_absolute_error
0.48861238171727794
mean_prior_absolute_error
0.48862652068817236
mean_prior_absolute_error
0.48862652068817236
mean_prior_absolute_error
0.48862652068817236
mean_prior_absolute_error
0.48862652068817236
mean_prior_absolute_error
0.48862652068817236
mean_prior_absolute_error
0.4885932162099533
mean_prior_absolute_error
0.4885932162099533
mean_prior_absolute_error
0.4885932162099533
number_of_instances
4532 [1924,2608]
number_of_instances
4532 [1924,2608]
number_of_instances
4531 [1924,2607]
number_of_instances
4531 [1924,2607]
number_of_instances
4531 [1924,2607]
number_of_instances
4531 [1924,2607]
number_of_instances
4531 [1924,2607]
number_of_instances
4531 [1923,2608]
number_of_instances
4531 [1923,2608]
number_of_instances
4531 [1923,2608]
precision
0.7624581522137451 [0.774722,0.753411]
precision
0.7631725777512304 [0.773316,0.755689]
precision
0.7503002961495921 [0.759577,0.743454]
precision
0.7609280467976299 [0.765526,0.757535]
precision
0.7580830871182807 [0.773826,0.746465]
precision
0.7622274885408521 [0.775873,0.752157]
precision
0.7745416948263858 [0.783681,0.767797]
precision
0.7679128466230305 [0.781699,0.757747]
precision
0.7535768200028308 [0.764045,0.745858]
precision
0.7613441665168738 [0.772549,0.753082]
predictive_accuracy
0.7605913503971756
predictive_accuracy
0.7616946160635482
predictive_accuracy
0.7488413153829176
predictive_accuracy
0.7603178106378283
predictive_accuracy
0.7554623703376738
predictive_accuracy
0.7600971088060031
predictive_accuracy
0.7733392187155154
predictive_accuracy
0.7658353564334583
predictive_accuracy
0.7519311410284705
predictive_accuracy
0.7596557051423527
prior_entropy
0.9835055532661361
prior_entropy
0.9835055532661361
prior_entropy
0.98354666368022
prior_entropy
0.98354666368022
prior_entropy
0.98354666368022
prior_entropy
0.98354666368022
prior_entropy
0.98354666368022
prior_entropy
0.9834498277152368
prior_entropy
0.9834498277152368
prior_entropy
0.9834498277152368
relative_absolute_error
0.6874971454458837
relative_absolute_error
0.6891052475025955
relative_absolute_error
0.7015512229067958
relative_absolute_error
0.6830177090577605
relative_absolute_error
0.683244083314998
relative_absolute_error
0.6894791011290099
relative_absolute_error
0.6732671348437674
relative_absolute_error
0.6778297897375246
relative_absolute_error
0.6927637136220909
relative_absolute_error
0.6797813877654048
root_mean_prior_squared_error
0.49427247515480305
root_mean_prior_squared_error
0.49427247515480305
root_mean_prior_squared_error
0.4942867777581652
root_mean_prior_squared_error
0.4942867777581652
root_mean_prior_squared_error
0.4942867777581652
root_mean_prior_squared_error
0.4942867777581652
root_mean_prior_squared_error
0.4942867777581652
root_mean_prior_squared_error
0.494253087181386
root_mean_prior_squared_error
0.494253087181386
root_mean_prior_squared_error
0.494253087181386
root_mean_squared_error
0.4050011562536198
root_mean_squared_error
0.40768363474271235
root_mean_squared_error
0.4141177473334124
root_mean_squared_error
0.405264531764673
root_mean_squared_error
0.4055008052351971
root_mean_squared_error
0.408022999659291
root_mean_squared_error
0.3968559872508592
root_mean_squared_error
0.4019627312579396
root_mean_squared_error
0.409717014752973
root_mean_squared_error
0.40360019911943856
root_relative_squared_error
0.8193884478935957
root_relative_squared_error
0.824815572857923
root_relative_squared_error
0.8378086689100627
root_relative_squared_error
0.8198975776830363
root_relative_squared_error
0.820375586566049
root_relative_squared_error
0.8254782810697
root_relative_squared_error
0.8028861080419695
root_relative_squared_error
0.8132730815102086
root_relative_squared_error
0.8289619738937734
root_relative_squared_error
0.8165860964492495
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
0.7414815121870337 [0.614865,0.868098]
unweighted_recall
0.7431898332971953 [0.620582,0.865798]
unweighted_recall
0.72904450436096 [0.597713,0.860376]
unweighted_recall
0.7429665214475341 [0.627859,0.858074]
unweighted_recall
0.7350024960784455 [0.599272,0.870733]
unweighted_recall
0.7406641283223562 [0.611746,0.869582]
unweighted_recall
0.7563928117725587 [0.643971,0.868815]
unweighted_recall
0.7469386965662675 [0.621945,0.871933]
unweighted_recall
0.7321287713471729 [0.601144,0.863113]
unweighted_recall
0.7406145018806887 [0.614665,0.866564]
usercpu_time_millis
314.66999999975087
usercpu_time_millis
364.57399999926565
usercpu_time_millis
357.63999999926455
usercpu_time_millis
381.6820000001826
usercpu_time_millis
402.4760000002061
usercpu_time_millis
355.4839999997057
usercpu_time_millis
347.4800000003597
usercpu_time_millis
351.7860000001747
usercpu_time_millis
355.46400000021094
usercpu_time_millis
325.71400000051653
usercpu_time_millis_testing
7.945999999719788
usercpu_time_millis_testing
8.441999999377003
usercpu_time_millis_testing
8.313999999700172
usercpu_time_millis_testing
7.278000000042084
usercpu_time_millis_testing
9.595999999874039
usercpu_time_millis_testing
7.206000000223867
usercpu_time_millis_testing
6.959999999708089
usercpu_time_millis_testing
7.324000000153319
usercpu_time_millis_testing
7.657999999537424
usercpu_time_millis_testing
7.006000000728818
usercpu_time_millis_training
306.7240000000311
usercpu_time_millis_training
356.13199999988865
usercpu_time_millis_training
349.3259999995644
usercpu_time_millis_training
374.4040000001405
usercpu_time_millis_training
392.8800000003321
usercpu_time_millis_training
348.27799999948184
usercpu_time_millis_training
340.52000000065163
usercpu_time_millis_training
344.46200000002136
usercpu_time_millis_training
347.8060000006735
usercpu_time_millis_training
318.7079999997877
wall_clock_time_millis
100.93092918395996
wall_clock_time_millis
93.12152862548828
wall_clock_time_millis
91.91393852233887
wall_clock_time_millis
97.29123115539551
wall_clock_time_millis
103.68728637695312
wall_clock_time_millis
93.22595596313477
wall_clock_time_millis
89.09201622009277
wall_clock_time_millis
90.58785438537598
wall_clock_time_millis
90.55376052856445
wall_clock_time_millis
85.09588241577148
wall_clock_time_millis_testing
2.0868778228759766
wall_clock_time_millis_testing
2.286672592163086
wall_clock_time_millis_testing
2.2449493408203125
wall_clock_time_millis_testing
1.8532276153564453
wall_clock_time_millis_testing
2.5610923767089844
wall_clock_time_millis_testing
1.8320083618164062
wall_clock_time_millis_testing
1.7490386962890625
wall_clock_time_millis_testing
1.8520355224609375
wall_clock_time_millis_testing
1.9848346710205078
wall_clock_time_millis_testing
1.7600059509277344
wall_clock_time_millis_training
98.84405136108398
wall_clock_time_millis_training
90.8348560333252
wall_clock_time_millis_training
89.66898918151855
wall_clock_time_millis_training
95.43800354003906
wall_clock_time_millis_training
101.12619400024414
wall_clock_time_millis_training
91.39394760131836
wall_clock_time_millis_training
87.34297752380371
wall_clock_time_millis_training
88.73581886291504
wall_clock_time_millis_training
88.56892585754395
wall_clock_time_millis_training
83.33587646484375
weighted_recall
0.7605913503971756 [0.614865,0.868098]
weighted_recall
0.7616946160635482 [0.620582,0.865798]
weighted_recall
0.7488413153829176 [0.597713,0.860376]
weighted_recall
0.7603178106378283 [0.627859,0.858074]
weighted_recall
0.7554623703376738 [0.599272,0.870733]
weighted_recall
0.7600971088060031 [0.611746,0.869582]
weighted_recall
0.7733392187155154 [0.643971,0.868815]
weighted_recall
0.7658353564334583 [0.621945,0.871933]
weighted_recall
0.7519311410284706 [0.601144,0.863113]
weighted_recall
0.7596557051423527 [0.614665,0.866564]