10559614
8323
Heinrich Peters
125920
Supervised Classification
18298
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)),svc=sklearn.svm.classes.SVC)(4)
8276193
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
20782.267317842347
17495
cache_size
200
17495
class_weight
null
17495
coef0
-0.3671201161021156
17495
decision_function_shape
"ovr"
17495
degree
5
17495
gamma
0.10680238302677152
17495
kernel
"rbf"
17495
max_iter
-1
17495
probability
true
17495
random_state
1
17495
shrinking
true
17495
tol
0.001
17495
verbose
false
17495
memory
null
18298
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": "svc", "step_name": "svc"}}]
18298
verbose
false
18298
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
openml-python
Sklearn_0.21.2.
23381
dresses-sales
https://www.openml.org/data/download/1910507/phpcFPMhq
-1
22044215
description
https://api.openml.org/data/download/22044215/description.xml
-1
22044216
predictions
https://api.openml.org/data/download/22044216/predictions.arff
area_under_roc_curve
0.5647619047619048 [0.564762,0.564762]
average_cost
0
f_measure
0.48716577540106953 [0.719251,0.166667]
kappa
0.03100775193798451
kb_relative_information_score
0.013906806124556732
mean_absolute_error
0.48133079582055904
mean_prior_absolute_error
0.4872509960159361
weighted_recall
0.58 [0.927586,0.1]
number_of_instances
500 [290,210]
precision
0.5506550218340611 [0.587336,0.5]
predictive_accuracy
0.58
prior_entropy
0.9814541958069474
relative_absolute_error
0.9878497935483268
root_mean_prior_squared_error
0.4935586100816085
root_mean_squared_error
0.4940251699120177
root_relative_squared_error
1.0009452977232676
total_cost
0
unweighted_recall
0.5137931034482759 [0.927586,0.1]
area_under_roc_curve
0.5139573070607554 [0.513957,0.513957]
area_under_roc_curve
0.5993431855500821 [0.599343,0.599343]
area_under_roc_curve
0.5188834154351396 [0.518883,0.518883]
area_under_roc_curve
0.43513957307060763 [0.43514,0.43514]
area_under_roc_curve
0.6486042692939245 [0.648604,0.648604]
area_under_roc_curve
0.5385878489326765 [0.538588,0.538588]
area_under_roc_curve
0.5188834154351396 [0.518883,0.518883]
area_under_roc_curve
0.7717569786535303 [0.771757,0.771757]
area_under_roc_curve
0.5632183908045977 [0.563218,0.563218]
area_under_roc_curve
0.5845648604269293 [0.584565,0.584565]
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
0.44710526315789473 [0.710526,0.083333]
f_measure
0.45833992094861664 [0.727273,0.086957]
f_measure
0.45833992094861664 [0.727273,0.086957]
f_measure
0.4654002713704206 [0.626866,0.242424]
f_measure
0.568149688149688 [0.756757,0.307692]
f_measure
0.44666666666666666 [0.666667,0.142857]
f_measure
0.48480000000000006 [0.72,0.16]
f_measure
0.5099265951439864 [0.753247,0.173913]
f_measure
0.5338666666666666 [0.746667,0.24]
f_measure
0.46946386946386953 [0.74359,0.090909]
kappa
-0.024208566108007368
kappa
0.01500938086303931
kappa
0.01500938086303931
kappa
-0.09075043630017444
kappa
0.1743119266055047
kappa
-0.08499095840867985
kappa
0.02957486136783716
kappa
0.10881801125703564
kappa
0.12199630314232894
kappa
0.05482041587901701
kb_relative_information_score
-0.0021075384813014856
kb_relative_information_score
0.013789933462392247
kb_relative_information_score
0.0008272962105205287
kb_relative_information_score
-0.029011805981866843
kb_relative_information_score
0.05634238771369118
kb_relative_information_score
0.013108119692660423
kb_relative_information_score
0.007234998538912851
kb_relative_information_score
0.05093425157219343
kb_relative_information_score
0.012149499815770683
kb_relative_information_score
0.015800918702593994
mean_absolute_error
0.4878134131453294
mean_absolute_error
0.48088414292224213
mean_absolute_error
0.4862822642711032
mean_absolute_error
0.4965660988689361
mean_absolute_error
0.4643668171078992
mean_absolute_error
0.48137019047110635
mean_absolute_error
0.4832398752202272
mean_absolute_error
0.4688125357295601
mean_absolute_error
0.4829384967166297
mean_absolute_error
0.48103412375255883
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
0.47319148936170213 [0.574468,0.333333]
precision
0.5483333333333333 [0.583333,0.5]
precision
0.5483333333333333 [0.583333,0.5]
precision
0.4605263157894737 [0.552632,0.333333]
precision
0.696888888888889 [0.622222,0.8]
precision
0.44372093023255815 [0.55814,0.285714]
precision
0.5504347826086957 [0.586957,0.5]
precision
0.7704166666666665 [0.604167,1]
precision
0.6680434782608696 [0.608696,0.75]
precision
0.7632653061224489 [0.591837,1]
predictive_accuracy
0.56
predictive_accuracy
0.58
predictive_accuracy
0.58
predictive_accuracy
0.5
predictive_accuracy
0.64
predictive_accuracy
0.52
predictive_accuracy
0.58
predictive_accuracy
0.62
predictive_accuracy
0.62
predictive_accuracy
0.6
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
1.0011542657357129
relative_absolute_error
0.9869331142557872
relative_absolute_error
0.9980118424533679
relative_absolute_error
1.0191176681611036
relative_absolute_error
0.9530341054299485
relative_absolute_error
0.9879306443846909
relative_absolute_error
0.9917678551126494
relative_absolute_error
0.9621581886191299
relative_absolute_error
0.9911493268673267
relative_absolute_error
0.9872409244635508
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
0.4974360609982473
root_mean_squared_error
0.48870964866327393
root_mean_squared_error
0.495269776400764
root_mean_squared_error
0.5276040729330969
root_mean_squared_error
0.4771416482282496
root_mean_squared_error
0.4970834037993564
root_mean_squared_error
0.4968391839445029
root_mean_squared_error
0.47509522762856604
root_mean_squared_error
0.49173172403021226
root_mean_squared_error
0.4914772824391448
root_relative_squared_error
1.0078561103735943
root_relative_squared_error
0.9901755104271557
root_relative_squared_error
1.003466997199933
root_relative_squared_error
1.0689795743728578
root_relative_squared_error
0.966737563648937
root_relative_squared_error
1.0071415909797732
root_relative_squared_error
1.0066467766864653
root_relative_squared_error
0.962591307139816
root_relative_squared_error
0.9962985428395345
root_relative_squared_error
0.995783018267842
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
0.4893267651888341 [0.931034,0.047619]
unweighted_recall
0.506568144499179 [0.965517,0.047619]
unweighted_recall
0.506568144499179 [0.965517,0.047619]
unweighted_recall
0.4573070607553366 [0.724138,0.190476]
unweighted_recall
0.5779967159277504 [0.965517,0.190476]
unweighted_recall
0.4614121510673235 [0.827586,0.095238]
unweighted_recall
0.513136288998358 [0.931034,0.095238]
unweighted_recall
0.5476190476190477 [1,0.095238]
unweighted_recall
0.5541871921182266 [0.965517,0.142857]
unweighted_recall
0.5238095238095238 [1,0.047619]
usercpu_time_millis
181.97200000000004
usercpu_time_millis
181.9779999999991
usercpu_time_millis
179.19400000000073
usercpu_time_millis
185.92600000000027
usercpu_time_millis
178.57599999999786
usercpu_time_millis
187.4959999999959
usercpu_time_millis
173.79999999999995
usercpu_time_millis
179.72999999999928
usercpu_time_millis
178.92600000000058
usercpu_time_millis
175.70199999999758
usercpu_time_millis_testing
6.918000000000646
usercpu_time_millis_testing
7.359999999998479
usercpu_time_millis_testing
7.200000000000983
usercpu_time_millis_testing
7.464000000000581
usercpu_time_millis_testing
7.258000000000209
usercpu_time_millis_testing
7.327999999997559
usercpu_time_millis_testing
7.376000000000715
usercpu_time_millis_testing
6.8139999999985434
usercpu_time_millis_testing
7.211999999999108
usercpu_time_millis_testing
6.807999999999481
usercpu_time_millis_training
175.05399999999938
usercpu_time_millis_training
174.61800000000062
usercpu_time_millis_training
171.99399999999974
usercpu_time_millis_training
178.46199999999968
usercpu_time_millis_training
171.31799999999765
usercpu_time_millis_training
180.16799999999833
usercpu_time_millis_training
166.42399999999924
usercpu_time_millis_training
172.91600000000074
usercpu_time_millis_training
171.71400000000148
usercpu_time_millis_training
168.8939999999981
wall_clock_time_millis
91.4926528930664
wall_clock_time_millis
90.85917472839355
wall_clock_time_millis
89.91074562072754
wall_clock_time_millis
93.18733215332031
wall_clock_time_millis
89.73193168640137
wall_clock_time_millis
94.12312507629395
wall_clock_time_millis
87.2197151184082
wall_clock_time_millis
90.42024612426758
wall_clock_time_millis
89.70117568969727
wall_clock_time_millis
88.04106712341309
wall_clock_time_millis_testing
3.4627914428710938
wall_clock_time_millis_testing
3.6869049072265625
wall_clock_time_millis_testing
3.634929656982422
wall_clock_time_millis_testing
3.7381649017333984
wall_clock_time_millis_testing
3.654003143310547
wall_clock_time_millis_testing
3.6962032318115234
wall_clock_time_millis_testing
3.6928653717041016
wall_clock_time_millis_testing
3.4110546112060547
wall_clock_time_millis_testing
3.6101341247558594
wall_clock_time_millis_testing
3.412961959838867
wall_clock_time_millis_training
88.02986145019531
wall_clock_time_millis_training
87.17226982116699
wall_clock_time_millis_training
86.27581596374512
wall_clock_time_millis_training
89.44916725158691
wall_clock_time_millis_training
86.07792854309082
wall_clock_time_millis_training
90.42692184448242
wall_clock_time_millis_training
83.5268497467041
wall_clock_time_millis_training
87.00919151306152
wall_clock_time_millis_training
86.0910415649414
wall_clock_time_millis_training
84.62810516357422
weighted_recall
0.56 [0.931034,0.047619]
weighted_recall
0.58 [0.965517,0.047619]
weighted_recall
0.58 [0.965517,0.047619]
weighted_recall
0.5 [0.724138,0.190476]
weighted_recall
0.64 [0.965517,0.190476]
weighted_recall
0.52 [0.827586,0.095238]
weighted_recall
0.58 [0.931034,0.095238]
weighted_recall
0.62 [1,0.095238]
weighted_recall
0.62 [0.965517,0.142857]
weighted_recall
0.6 [1,0.047619]