10553031
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)
8275720
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
1.0
17462
class_weight
null
17462
dual
false
17462
fit_intercept
true
17462
intercept_scaling
1
17462
l1_ratio
null
17462
max_iter
100
17462
multi_class
"warn"
17462
n_jobs
null
17462
penalty
"l2"
17462
random_state
1
17462
solver
"warn"
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
22031017
description
https://api.openml.org/data/download/22031017/description.xml
-1
22031018
predictions
https://api.openml.org/data/download/22031018/predictions.arff
area_under_roc_curve
0.8273440678470415 [0.827344,0.827344]
average_cost
0
f_measure
0.7564233266357969 [0.689128,0.806071]
kappa
0.4986535101240343
kb_relative_information_score
0.35337887452152894
mean_absolute_error
0.3293994422436843
mean_prior_absolute_error
0.4886137014923867
weighted_recall
0.7611449505649718 [0.62359,0.862627]
number_of_instances
45312 [19237,26075]
precision
0.7622420587730101 [0.77006,0.756474]
predictive_accuracy
0.7611449505649718
prior_entropy
0.9835093906388539
relative_absolute_error
0.6741510547853861
root_mean_prior_squared_error
0.4942738102212943
root_mean_squared_error
0.4055035153279296
root_relative_squared_error
0.8204025925354596
total_cost
0
unweighted_recall
0.7431084971230587 [0.62359,0.862627]
area_under_roc_curve
0.8283551809241994 [0.828355,0.828355]
area_under_roc_curve
0.8234603985179139 [0.82346,0.82346]
area_under_roc_curve
0.8143447953574536 [0.814345,0.814345]
area_under_roc_curve
0.8284879107663918 [0.828488,0.828488]
area_under_roc_curve
0.8285214044707716 [0.828521,0.828521]
area_under_roc_curve
0.8218481826076762 [0.821848,0.821848]
area_under_roc_curve
0.8414300376325694 [0.84143,0.84143]
area_under_roc_curve
0.8349579995469757 [0.834958,0.834958]
area_under_roc_curve
0.8206654033032487 [0.820665,0.820665]
area_under_roc_curve
0.8319654872084455 [0.831965,0.831965]
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
0.7587117755354916 [0.691777,0.808092]
f_measure
0.7587515070056734 [0.692814,0.807395]
f_measure
0.7472544379293273 [0.676657,0.799356]
f_measure
0.7558283698835256 [0.691085,0.80361]
f_measure
0.7510600510979292 [0.679826,0.803632]
f_measure
0.7557997887831432 [0.686723,0.80678]
f_measure
0.7701710596265561 [0.710042,0.814547]
f_measure
0.7625622330174016 [0.696078,0.811584]
f_measure
0.7493831391996889 [0.678798,0.801429]
f_measure
0.7545362375984936 [0.686944,0.804375]
kappa
0.5033680538234383
kappa
0.5034255905687096
kappa
0.4798434797876147
kappa
0.4974320726168148
kappa
0.487756914963347
kappa
0.49746725008891746
kappa
0.5269611590272805
kappa
0.5112619043379285
kappa
0.4841504247630468
kappa
0.4947072410609212
kb_relative_information_score
0.3523206487642655
kb_relative_information_score
0.34983660075492584
kb_relative_information_score
0.335536652824943
kb_relative_information_score
0.3561309219099662
kb_relative_information_score
0.35527986495587155
kb_relative_information_score
0.3494489746339163
kb_relative_information_score
0.36854258209968854
kb_relative_information_score
0.3630183149859962
kb_relative_information_score
0.3446031266817122
kb_relative_information_score
0.3590725262183557
mean_absolute_error
0.3302133852265749
mean_absolute_error
0.3311892498188058
mean_absolute_error
0.3371924951297387
mean_absolute_error
0.3279686302393491
mean_absolute_error
0.3281585886356631
mean_absolute_error
0.33137180325724014
mean_absolute_error
0.3230971006054141
mean_absolute_error
0.3251973295273277
mean_absolute_error
0.3331336119946987
mean_absolute_error
0.3264716533494932
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
0.7647857075537084 [0.774131,0.757891]
precision
0.7641920034365911 [0.771192,0.759028]
precision
0.7532597997150713 [0.759379,0.748744]
precision
0.7600654229790151 [0.761577,0.75895]
precision
0.7583495698050214 [0.769888,0.749834]
precision
0.7627169635604316 [0.774299,0.754169]
precision
0.7743421594210912 [0.779019,0.77089]
precision
0.769133488475952 [0.78123,0.760214]
precision
0.7557222220071133 [0.763483,0.75]
precision
0.7600789168562951 [0.766325,0.755473]
predictive_accuracy
0.7634598411297441
predictive_accuracy
0.7632391879964696
predictive_accuracy
0.7523725446921209
predictive_accuracy
0.7598764069741779
predictive_accuracy
0.7565658794967999
predictive_accuracy
0.760979916133304
predictive_accuracy
0.7737806223791658
predictive_accuracy
0.7673802692562348
predictive_accuracy
0.754579563010373
predictive_accuracy
0.7592143014787023
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
0.6758187012494574
relative_absolute_error
0.6778159175066492
relative_absolute_error
0.6900822629415266
relative_absolute_error
0.6712051359337685
relative_absolute_error
0.6715938958317096
relative_absolute_error
0.6781699093830241
relative_absolute_error
0.6612352930626243
relative_absolute_error
0.6655788879958319
relative_absolute_error
0.681822016643694
relative_absolute_error
0.6681870368196131
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
0.40453768964585907
root_mean_squared_error
0.4075663150700419
root_mean_squared_error
0.4138279162814279
root_mean_squared_error
0.40505361750753355
root_mean_squared_error
0.4051835683390439
root_mean_squared_error
0.40784911893673675
root_mean_squared_error
0.39619665477765104
root_mean_squared_error
0.40138594972221614
root_mean_squared_error
0.40962169905262424
root_mean_squared_error
0.40356010329410025
root_relative_squared_error
0.8184507735721281
root_relative_squared_error
0.824578214561502
root_relative_squared_error
0.8372223067716721
root_relative_squared_error
0.8194708734566031
root_relative_squared_error
0.8197337791974765
root_relative_squared_error
0.8251265000179329
root_relative_squared_error
0.8015522012840373
root_relative_squared_error
0.812106105419047
root_relative_squared_error
0.8287691259322315
root_relative_squared_error
0.8165049723725807
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
0.7453369928446616 [0.62526,0.865414]
unweighted_recall
0.7456223773325 [0.628898,0.862347]
unweighted_recall
0.7337471799497115 [0.610187,0.857307]
unweighted_recall
0.7431956941450613 [0.632536,0.853855]
unweighted_recall
0.7371869634527862 [0.608628,0.865746]
unweighted_recall
0.7421121329349177 [0.616944,0.86728]
unweighted_recall
0.7578657372961171 [0.652287,0.863445]
unweighted_recall
0.7490319398051997 [0.627665,0.870399]
unweighted_recall
0.7357269444151999 [0.611024,0.860429]
unweighted_recall
0.7412554554329411 [0.622465,0.860046]
usercpu_time_millis
203.54000000043015
usercpu_time_millis
373.06599999919854
usercpu_time_millis
373.1019999995624
usercpu_time_millis
393.02799999950366
usercpu_time_millis
378.48399999893445
usercpu_time_millis
398.5979999997653
usercpu_time_millis
398.152000000664
usercpu_time_millis
394.34199999959674
usercpu_time_millis
224.10599999966507
usercpu_time_millis
387.36599999901955
usercpu_time_millis_testing
5.992000000333064
usercpu_time_millis_testing
7.541999999375548
usercpu_time_millis_testing
8.052000000134285
usercpu_time_millis_testing
8.257999999841559
usercpu_time_millis_testing
8.105999999315827
usercpu_time_millis_testing
8.041999999477412
usercpu_time_millis_testing
8.384000000660308
usercpu_time_millis_testing
8.029999999962456
usercpu_time_millis_testing
4.3759999998655985
usercpu_time_millis_testing
8.259999999609136
usercpu_time_millis_training
197.5480000000971
usercpu_time_millis_training
365.523999999823
usercpu_time_millis_training
365.0499999994281
usercpu_time_millis_training
384.7699999996621
usercpu_time_millis_training
370.3779999996186
usercpu_time_millis_training
390.5560000002879
usercpu_time_millis_training
389.76800000000367
usercpu_time_millis_training
386.3119999996343
usercpu_time_millis_training
219.72999999979947
usercpu_time_millis_training
379.1059999994104
wall_clock_time_millis
109.63177680969238
wall_clock_time_millis
97.24187850952148
wall_clock_time_millis
95.68119049072266
wall_clock_time_millis
101.22489929199219
wall_clock_time_millis
97.43261337280273
wall_clock_time_millis
102.37860679626465
wall_clock_time_millis
111.0842227935791
wall_clock_time_millis
101.57227516174316
wall_clock_time_millis
96.08316421508789
wall_clock_time_millis
100.20089149475098
wall_clock_time_millis_testing
3.160715103149414
wall_clock_time_millis_testing
1.8928050994873047
wall_clock_time_millis_testing
2.109050750732422
wall_clock_time_millis_testing
2.1820068359375
wall_clock_time_millis_testing
2.136707305908203
wall_clock_time_millis_testing
2.1147727966308594
wall_clock_time_millis_testing
2.206087112426758
wall_clock_time_millis_testing
2.1042823791503906
wall_clock_time_millis_testing
2.292156219482422
wall_clock_time_millis_testing
2.1800994873046875
wall_clock_time_millis_training
106.47106170654297
wall_clock_time_millis_training
95.34907341003418
wall_clock_time_millis_training
93.57213973999023
wall_clock_time_millis_training
99.04289245605469
wall_clock_time_millis_training
95.29590606689453
wall_clock_time_millis_training
100.26383399963379
wall_clock_time_millis_training
108.87813568115234
wall_clock_time_millis_training
99.46799278259277
wall_clock_time_millis_training
93.79100799560547
wall_clock_time_millis_training
98.02079200744629
weighted_recall
0.7634598411297441 [0.62526,0.865414]
weighted_recall
0.7632391879964695 [0.628898,0.862347]
weighted_recall
0.7523725446921209 [0.610187,0.857307]
weighted_recall
0.7598764069741779 [0.632536,0.853855]
weighted_recall
0.7565658794967999 [0.608628,0.865746]
weighted_recall
0.760979916133304 [0.616944,0.86728]
weighted_recall
0.7737806223791658 [0.652287,0.863445]
weighted_recall
0.7673802692562348 [0.627665,0.870399]
weighted_recall
0.754579563010373 [0.611024,0.860429]
weighted_recall
0.7592143014787023 [0.622465,0.860046]