10558897
8323
Heinrich Peters
125920
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)
8275996
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
0.1
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
"auto"
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": [false, false, true, false, false, false, false, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, true, false, true, true, true, true, true, true, true, true, true]}}]
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.
23381
dresses-sales
https://www.openml.org/data/download/1910507/phpcFPMhq
-1
22042758
description
https://api.openml.org/data/download/22042758/description.xml
-1
22042759
predictions
https://api.openml.org/data/download/22042759/predictions.arff
area_under_roc_curve
0.654712643678161 [0.654713,0.654713]
average_cost
0
f_measure
0.6135418900938505 [0.722307,0.463343]
kappa
0.2076550051957049
kb_relative_information_score
0.08551851860045032
mean_absolute_error
0.4517034079025114
mean_prior_absolute_error
0.4872509960159361
weighted_recall
0.634 [0.82069,0.37619]
number_of_instances
500 [290,210]
precision
0.6273745836695008 [0.644986,0.603053]
predictive_accuracy
0.634
prior_entropy
0.9814541958069474
relative_absolute_error
0.9270446065701585
root_mean_prior_squared_error
0.4935586100816085
root_mean_squared_error
0.47636297406634914
root_relative_squared_error
0.9651598905094247
total_cost
0
unweighted_recall
0.598440065681445 [0.82069,0.37619]
area_under_roc_curve
0.6059113300492611 [0.605911,0.605911]
area_under_roc_curve
0.7159277504105092 [0.715928,0.715928]
area_under_roc_curve
0.6486042692939245 [0.648604,0.648604]
area_under_roc_curve
0.573070607553366 [0.573071,0.573071]
area_under_roc_curve
0.6551724137931035 [0.655172,0.655172]
area_under_roc_curve
0.6995073891625617 [0.699507,0.699507]
area_under_roc_curve
0.6847290640394089 [0.684729,0.684729]
area_under_roc_curve
0.7602627257799671 [0.760263,0.760263]
area_under_roc_curve
0.5238095238095238 [0.52381,0.52381]
area_under_roc_curve
0.6880131362889983 [0.688013,0.688013]
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
0.6024615384615384 [0.707692,0.457143]
f_measure
0.728 [0.8,0.628571]
f_measure
0.49277777777777787 [0.694444,0.214286]
f_measure
0.5771836007130124 [0.69697,0.411765]
f_measure
0.5771836007130124 [0.69697,0.411765]
f_measure
0.636472184531886 [0.746269,0.484848]
f_measure
0.6706872370266478 [0.782609,0.516129]
f_measure
0.6773333333333333 [0.733333,0.6]
f_measure
0.5187692307692308 [0.646154,0.342857]
f_measure
0.626875 [0.71875,0.5]
kappa
0.18244406196213422
kappa
0.44061962134251287
kappa
0.005424954792043555
kappa
0.1334488734835355
kappa
0.1334488734835355
kappa
0.25828970331588147
kappa
0.3362831858407078
kappa
0.33444259567387696
kappa
0.010327022375215203
kappa
0.23076923076923075
kb_relative_information_score
0.07464048567379286
kb_relative_information_score
0.14652471800690692
kb_relative_information_score
0.07244079414232346
kb_relative_information_score
0.05267708977482838
kb_relative_information_score
0.09883321472706198
kb_relative_information_score
0.08418575007202238
kb_relative_information_score
0.09150807378405994
kb_relative_information_score
0.16098237475077212
kb_relative_information_score
-0.006644848821835128
kb_relative_information_score
0.08003753389456797
mean_absolute_error
0.4577410862938413
mean_absolute_error
0.4295430871125894
mean_absolute_error
0.4556902089353328
mean_absolute_error
0.46459350087214446
mean_absolute_error
0.44441309884013286
mean_absolute_error
0.4523691003425862
mean_absolute_error
0.4513094237577465
mean_absolute_error
0.41997259590242214
mean_absolute_error
0.48711397720495697
mean_absolute_error
0.45428799976336287
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
mean_prior_absolute_error
0.48725099601593624
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
number_of_instances
50 [29,21]
precision
0.6105555555555555 [0.638889,0.571429]
precision
0.7488888888888888 [0.722222,0.785714]
precision
0.5172093023255814 [0.581395,0.428571]
precision
0.5866943866943867 [0.621622,0.538462]
precision
0.5866943866943867 [0.621622,0.538462]
precision
0.661578947368421 [0.657895,0.666667]
precision
0.7275 [0.675,0.8]
precision
0.6768760611205432 [0.709677,0.631579]
precision
0.5183333333333333 [0.583333,0.428571]
precision
0.6331428571428571 [0.657143,0.6]
predictive_accuracy
0.62
predictive_accuracy
0.74
predictive_accuracy
0.56
predictive_accuracy
0.6
predictive_accuracy
0.6
predictive_accuracy
0.66
predictive_accuracy
0.7
predictive_accuracy
0.68
predictive_accuracy
0.54
predictive_accuracy
0.64
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
prior_entropy
0.9814541958069504
relative_absolute_error
0.939435917087115
relative_absolute_error
0.881564307974325
relative_absolute_error
0.9352268392703887
relative_absolute_error
0.9534993353958157
relative_absolute_error
0.912082484128155
relative_absolute_error
0.9284108273588646
relative_absolute_error
0.9262360209582533
relative_absolute_error
0.8619224985405394
relative_absolute_error
0.9997187921377285
relative_absolute_error
0.9323490428504013
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_prior_squared_error
0.49355861008160823
root_mean_squared_error
0.4845822942530337
root_mean_squared_error
0.4574091025661922
root_mean_squared_error
0.4797677063208944
root_mean_squared_error
0.49152835886085466
root_mean_squared_error
0.47154302135732473
root_mean_squared_error
0.47931229428311994
root_mean_squared_error
0.4692285772466302
root_mean_squared_error
0.44817007427691424
root_mean_squared_error
0.5047167186139159
root_mean_squared_error
0.4749027567135817
root_relative_squared_error
0.9818130701294211
root_relative_squared_error
0.9267574168963665
root_relative_squared_error
0.9720582247396443
root_relative_squared_error
0.9958865042990176
root_relative_squared_error
0.9553941755354175
root_relative_squared_error
0.9711355135793646
root_relative_squared_error
0.9507048761018368
root_relative_squared_error
0.908038204830042
root_relative_squared_error
1.0226074640465956
root_relative_squared_error
0.9622013414679528
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
0.5870279146141215 [0.793103,0.380952]
unweighted_recall
0.7101806239737274 [0.896552,0.52381]
unweighted_recall
0.5024630541871921 [0.862069,0.142857]
unweighted_recall
0.5632183908045977 [0.793103,0.333333]
unweighted_recall
0.5632183908045977 [0.793103,0.333333]
unweighted_recall
0.6215106732348111 [0.862069,0.380952]
unweighted_recall
0.6559934318555007 [0.931034,0.380952]
unweighted_recall
0.6650246305418719 [0.758621,0.571429]
unweighted_recall
0.5049261083743842 [0.724138,0.285714]
unweighted_recall
0.6108374384236454 [0.793103,0.428571]
usercpu_time_millis
40.162000001146225
usercpu_time_millis
40.89200000089477
usercpu_time_millis
37.23399999944377
usercpu_time_millis
37.43000000031316
usercpu_time_millis
39.6599999985483
usercpu_time_millis
39.98200000205543
usercpu_time_millis
37.23600000012084
usercpu_time_millis
39.919999999256106
usercpu_time_millis
39.24800000095274
usercpu_time_millis
41.1260000000766
usercpu_time_millis_testing
8.608000000094762
usercpu_time_millis_testing
8.187999999790918
usercpu_time_millis_testing
5.185999998502666
usercpu_time_millis_testing
5.2500000019790605
usercpu_time_millis_testing
10.033999998995569
usercpu_time_millis_testing
6.3599999994039536
usercpu_time_millis_testing
6.313999998383224
usercpu_time_millis_testing
4.9360000011802185
usercpu_time_millis_testing
7.592000001750421
usercpu_time_millis_testing
8.003999999345979
usercpu_time_millis_training
31.554000001051463
usercpu_time_millis_training
32.70400000110385
usercpu_time_millis_training
32.0480000009411
usercpu_time_millis_training
32.1799999983341
usercpu_time_millis_training
29.625999999552732
usercpu_time_millis_training
33.622000002651475
usercpu_time_millis_training
30.922000001737615
usercpu_time_millis_training
34.98399999807589
usercpu_time_millis_training
31.655999999202322
usercpu_time_millis_training
33.12200000073062
wall_clock_time_millis
23.880720138549805
wall_clock_time_millis
21.39592170715332
wall_clock_time_millis
19.69599723815918
wall_clock_time_millis
19.37699317932129
wall_clock_time_millis
23.905038833618164
wall_clock_time_millis
23.95915985107422
wall_clock_time_millis
23.044347763061523
wall_clock_time_millis
29.706954956054688
wall_clock_time_millis
26.088953018188477
wall_clock_time_millis
21.913766860961914
wall_clock_time_millis_testing
5.0048828125
wall_clock_time_millis_testing
4.123926162719727
wall_clock_time_millis_testing
2.619028091430664
wall_clock_time_millis_testing
2.6388168334960938
wall_clock_time_millis_testing
7.992029190063477
wall_clock_time_millis_testing
3.1921863555908203
wall_clock_time_millis_testing
3.5390853881835938
wall_clock_time_millis_testing
2.4728775024414062
wall_clock_time_millis_testing
8.831977844238281
wall_clock_time_millis_testing
4.23884391784668
wall_clock_time_millis_training
18.875837326049805
wall_clock_time_millis_training
17.271995544433594
wall_clock_time_millis_training
17.076969146728516
wall_clock_time_millis_training
16.738176345825195
wall_clock_time_millis_training
15.913009643554688
wall_clock_time_millis_training
20.7669734954834
wall_clock_time_millis_training
19.50526237487793
wall_clock_time_millis_training
27.23407745361328
wall_clock_time_millis_training
17.256975173950195
wall_clock_time_millis_training
17.674922943115234
weighted_recall
0.62 [0.793103,0.380952]
weighted_recall
0.74 [0.896552,0.52381]
weighted_recall
0.56 [0.862069,0.142857]
weighted_recall
0.6 [0.793103,0.333333]
weighted_recall
0.6 [0.793103,0.333333]
weighted_recall
0.66 [0.862069,0.380952]
weighted_recall
0.7 [0.931034,0.380952]
weighted_recall
0.68 [0.758621,0.571429]
weighted_recall
0.54 [0.724138,0.285714]
weighted_recall
0.64 [0.793103,0.428571]