10559556
8323
Heinrich Peters
14954
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)
8276168
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
13917.287565392886
17495
cache_size
200
17495
class_weight
null
17495
coef0
0.030380904322180546
17495
decision_function_shape
"ovr"
17495
degree
5
17495
gamma
0.0011255179130262153
17495
kernel
"poly"
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, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, 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.
6332
cylinder-bands
https://www.openml.org/data/download/1854224/phpAz9Len
-1
22044099
description
https://api.openml.org/data/download/22044099/description.xml
-1
22044100
predictions
https://api.openml.org/data/download/22044100/predictions.arff
area_under_roc_curve
0.813034188034188 [0.813034,0.813034]
average_cost
0
f_measure
0.740604489724695 [0.665037,0.795827]
kappa
0.46516873427604766
kb_relative_information_score
0.22502140282805697
mean_absolute_error
0.39370275038771246
mean_prior_absolute_error
0.48794587945879536
weighted_recall
0.7462962962962963 [0.596491,0.855769]
number_of_instances
540 [228,312]
precision
0.7469620099485133 [0.751381,0.743733]
predictive_accuracy
0.7462962962962963
prior_entropy
0.9824743303740947
relative_absolute_error
0.806857413827098
root_mean_prior_squared_error
0.49391365607219145
root_mean_squared_error
0.42907272031234606
root_relative_squared_error
0.8687200992264767
total_cost
0
unweighted_recall
0.7261302294197031 [0.596491,0.855769]
area_under_roc_curve
0.8653576437587658 [0.865358,0.865358]
area_under_roc_curve
0.8345021037868162 [0.834502,0.834502]
area_under_roc_curve
0.8520336605890604 [0.852034,0.852034]
area_under_roc_curve
0.6858345021037868 [0.685835,0.685835]
area_under_roc_curve
0.8106591865357644 [0.810659,0.810659]
area_under_roc_curve
0.7405329593267882 [0.740533,0.740533]
area_under_roc_curve
0.9172510518934082 [0.917251,0.917251]
area_under_roc_curve
0.7503506311360448 [0.750351,0.750351]
area_under_roc_curve
0.9019886363636362 [0.901989,0.901989]
area_under_roc_curve
0.7883522727272727 [0.788352,0.788352]
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
0.7452381959424211 [0.648649,0.816901]
f_measure
0.7761994949494949 [0.727273,0.8125]
f_measure
0.741820987654321 [0.708333,0.766667]
f_measure
0.5074735449735448 [0.214286,0.725]
f_measure
0.7227366255144033 [0.611111,0.805556]
f_measure
0.6608946608946609 [0.571429,0.727273]
f_measure
0.8880997474747474 [0.863636,0.90625]
f_measure
0.6985730319063653 [0.619048,0.757576]
f_measure
0.8110021786492374 [0.75,0.852941]
f_measure
0.7796296296296297 [0.75,0.8]
kappa
0.481536189069424
kappa
0.5404255319148936
kappa
0.47572815533980567
kappa
0.07332293291731665
kappa
0.43833580980683495
kappa
0.3027259684361549
kappa
0.7702127659574467
kappa
0.3802008608321378
kappa
0.6052631578947367
kappa
0.5524861878453039
kb_relative_information_score
0.1683543581408022
kb_relative_information_score
0.3362740521172612
kb_relative_information_score
0.2819411625511203
kb_relative_information_score
0.037751737994585234
kb_relative_information_score
0.21263000445703586
kb_relative_information_score
0.1635017975501772
kb_relative_information_score
0.3261336616342583
kb_relative_information_score
0.17539386075097643
kb_relative_information_score
0.2914232741905657
kb_relative_information_score
0.2576501892550309
mean_absolute_error
0.4241604198914865
mean_absolute_error
0.34116610450824253
mean_absolute_error
0.368007959407857
mean_absolute_error
0.47391685783496235
mean_absolute_error
0.4005521925245664
mean_absolute_error
0.41918172007950777
mean_absolute_error
0.3531335241753524
mean_absolute_error
0.41569110996395625
mean_absolute_error
0.36416375339907064
mean_absolute_error
0.3770538620921215
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.48851988519885264
mean_prior_absolute_error
0.4856498564985656
mean_prior_absolute_error
0.4856498564985656
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [23,31]
number_of_instances
54 [22,32]
number_of_instances
54 [22,32]
precision
0.7812830687830687 [0.857143,0.725]
precision
0.7768157768157766 [0.761905,0.787879]
precision
0.7449297573435506 [0.68,0.793103]
precision
0.5953136810279667 [0.6,0.591837]
precision
0.7664512542561324 [0.846154,0.707317]
precision
0.6626566416040099 [0.631579,0.685714]
precision
0.8898508898508899 [0.904762,0.878788]
precision
0.7014759120022278 [0.684211,0.714286]
precision
0.8168724279835392 [0.833333,0.805556]
precision
0.78998778998779 [0.692308,0.857143]
predictive_accuracy
0.7592592592592592
predictive_accuracy
0.7777777777777777
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.5925925925925926
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.6666666666666667
predictive_accuracy
0.8888888888888888
predictive_accuracy
0.7037037037037037
predictive_accuracy
0.8148148148148148
predictive_accuracy
0.7777777777777777
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9841440157771891
prior_entropy
0.9757955887617137
prior_entropy
0.9757955887617137
relative_absolute_error
0.8682562015235704
relative_absolute_error
0.6983668727617309
relative_absolute_error
0.7533121384773497
relative_absolute_error
0.9701076091141181
relative_absolute_error
0.8199301700104208
relative_absolute_error
0.8580648050977072
relative_absolute_error
0.7228641757983074
relative_absolute_error
0.8509195276559697
relative_absolute_error
0.7498483702324458
relative_absolute_error
0.7763903500571406
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.49449439369385695
root_mean_prior_squared_error
0.4915838450298872
root_mean_prior_squared_error
0.4915838450298872
root_mean_squared_error
0.44671768257190236
root_mean_squared_error
0.41204595950092093
root_mean_squared_error
0.4061000478825692
root_mean_squared_error
0.48237760411888303
root_mean_squared_error
0.4264888184437953
root_mean_squared_error
0.45147299156028786
root_mean_squared_error
0.3820900629147461
root_mean_squared_error
0.44928261324327107
root_mean_squared_error
0.3913978290074824
root_mean_squared_error
0.4328157956851525
root_relative_squared_error
0.903382704169679
root_relative_squared_error
0.8332672013184034
root_relative_squared_error
0.8212429767889078
root_relative_squared_error
0.9754966087998249
root_relative_squared_error
0.8624745272801533
root_relative_squared_error
0.9129992115538447
root_relative_squared_error
0.7726883616628002
root_relative_squared_error
0.9085696804106204
root_relative_squared_error
0.7961975011275771
root_relative_squared_error
0.8804516260269664
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
0.7286115007012622 [0.521739,0.935484]
unweighted_recall
0.7671809256661992 [0.695652,0.83871]
unweighted_recall
0.7405329593267882 [0.73913,0.741935]
unweighted_recall
0.5329593267882188 [0.130435,0.935484]
unweighted_recall
0.7068723702664796 [0.478261,0.935484]
unweighted_recall
0.6479663394109396 [0.521739,0.774194]
unweighted_recall
0.8807854137447405 [0.826087,0.935484]
unweighted_recall
0.6858345021037868 [0.565217,0.806452]
unweighted_recall
0.7940340909090908 [0.681818,0.90625]
unweighted_recall
0.7840909090909092 [0.818182,0.75]
usercpu_time_millis
220.7419999999729
usercpu_time_millis
217.99200000003793
usercpu_time_millis
218.35199999998167
usercpu_time_millis
219.28800000000592
usercpu_time_millis
217.9540000000202
usercpu_time_millis
225.06400000003168
usercpu_time_millis
221.8880000000354
usercpu_time_millis
231.22399999999743
usercpu_time_millis
230.69400000002815
usercpu_time_millis
217.736000000059
usercpu_time_millis_testing
10.503999999968983
usercpu_time_millis_testing
9.382000000016433
usercpu_time_millis_testing
10.14199999997345
usercpu_time_millis_testing
9.569999999996526
usercpu_time_millis_testing
9.47800000000143
usercpu_time_millis_testing
9.988000000021202
usercpu_time_millis_testing
9.948000000008506
usercpu_time_millis_testing
9.838000000002012
usercpu_time_millis_testing
9.410000000002583
usercpu_time_millis_testing
9.78000000003476
usercpu_time_millis_training
210.23800000000392
usercpu_time_millis_training
208.6100000000215
usercpu_time_millis_training
208.21000000000822
usercpu_time_millis_training
209.7180000000094
usercpu_time_millis_training
208.47600000001876
usercpu_time_millis_training
215.07600000001048
usercpu_time_millis_training
211.94000000002688
usercpu_time_millis_training
221.38599999999542
usercpu_time_millis_training
221.28400000002557
usercpu_time_millis_training
207.95600000002423
wall_clock_time_millis
110.43500900268555
wall_clock_time_millis
109.2989444732666
wall_clock_time_millis
109.5728874206543
wall_clock_time_millis
109.86900329589844
wall_clock_time_millis
109.26389694213867
wall_clock_time_millis
114.5172119140625
wall_clock_time_millis
111.21320724487305
wall_clock_time_millis
116.00589752197266
wall_clock_time_millis
115.52023887634277
wall_clock_time_millis
109.08222198486328
wall_clock_time_millis_testing
5.314111709594727
wall_clock_time_millis_testing
4.696846008300781
wall_clock_time_millis_testing
5.094766616821289
wall_clock_time_millis_testing
4.802942276000977
wall_clock_time_millis_testing
4.775047302246094
wall_clock_time_millis_testing
5.013942718505859
wall_clock_time_millis_testing
4.991054534912109
wall_clock_time_millis_testing
4.960060119628906
wall_clock_time_millis_testing
4.7130584716796875
wall_clock_time_millis_testing
4.91023063659668
wall_clock_time_millis_training
105.12089729309082
wall_clock_time_millis_training
104.60209846496582
wall_clock_time_millis_training
104.47812080383301
wall_clock_time_millis_training
105.06606101989746
wall_clock_time_millis_training
104.48884963989258
wall_clock_time_millis_training
109.50326919555664
wall_clock_time_millis_training
106.22215270996094
wall_clock_time_millis_training
111.04583740234375
wall_clock_time_millis_training
110.80718040466309
wall_clock_time_millis_training
104.1719913482666
weighted_recall
0.7592592592592593 [0.521739,0.935484]
weighted_recall
0.7777777777777778 [0.695652,0.83871]
weighted_recall
0.7407407407407407 [0.73913,0.741935]
weighted_recall
0.5925925925925926 [0.130435,0.935484]
weighted_recall
0.7407407407407407 [0.478261,0.935484]
weighted_recall
0.6666666666666666 [0.521739,0.774194]
weighted_recall
0.8888888888888888 [0.826087,0.935484]
weighted_recall
0.7037037037037037 [0.565217,0.806452]
weighted_recall
0.8148148148148148 [0.681818,0.90625]
weighted_recall
0.7777777777777778 [0.818182,0.75]