10559551
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)
8276164
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
690.6018801899403
17495
cache_size
200
17495
class_weight
null
17495
coef0
-0.6356144967116901
17495
decision_function_shape
"ovr"
17495
degree
5
17495
gamma
0.0008714226148272087
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, 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
22044089
description
https://api.openml.org/data/download/22044089/description.xml
-1
22044090
predictions
https://api.openml.org/data/download/22044090/predictions.arff
area_under_roc_curve
0.866860661268556 [0.866861,0.866861]
average_cost
0
f_measure
0.8061499215256738 [0.762557,0.838006]
kappa
0.6010230179028134
kb_relative_information_score
0.42943348044734087
mean_absolute_error
0.29304175341853306
mean_prior_absolute_error
0.48794587945879536
weighted_recall
0.8074074074074075 [0.732456,0.862179]
number_of_instances
540 [228,312]
precision
0.8067436267436268 [0.795238,0.815152]
predictive_accuracy
0.8074074074074075
prior_entropy
0.9824743303740947
relative_absolute_error
0.6005620003258558
root_mean_prior_squared_error
0.49391365607219145
root_mean_squared_error
0.3785097338535566
root_relative_squared_error
0.7663479824867058
total_cost
0
unweighted_recall
0.7973178137651822 [0.732456,0.862179]
area_under_roc_curve
0.8793828892005608 [0.879383,0.879383]
area_under_roc_curve
0.8751753155680225 [0.875175,0.875175]
area_under_roc_curve
0.9593267882187938 [0.959327,0.959327]
area_under_roc_curve
0.8302945301542777 [0.830295,0.830295]
area_under_roc_curve
0.8948106591865357 [0.894811,0.894811]
area_under_roc_curve
0.7896213183730715 [0.789621,0.789621]
area_under_roc_curve
0.9593267882187938 [0.959327,0.959327]
area_under_roc_curve
0.7573632538569425 [0.757363,0.757363]
area_under_roc_curve
0.9247159090909092 [0.924716,0.924716]
area_under_roc_curve
0.78125 [0.78125,0.78125]
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
0.8518518518518519 [0.826087,0.870968]
f_measure
0.7956496178718401 [0.755556,0.825397]
f_measure
0.9076334793111912 [0.893617,0.918033]
f_measure
0.8116081449414784 [0.761905,0.848485]
f_measure
0.7709150326797385 [0.7,0.823529]
f_measure
0.7362514029180696 [0.666667,0.787879]
f_measure
0.9259259259259259 [0.913043,0.935484]
f_measure
0.6859538296580502 [0.638298,0.721311]
f_measure
0.8309671156413055 [0.780488,0.865672]
f_measure
0.7384960718294052 [0.666667,0.787879]
kappa
0.697054698457223
kappa
0.5811001410437235
kappa
0.8117154811715482
kappa
0.612625538020086
kappa
0.5297532656023222
kappa
0.4576757532281205
kappa
0.8485273492286115
kappa
0.35983263598326376
kappa
0.6473149492017417
kappa
0.4553314121037463
kb_relative_information_score
0.48835447521127195
kb_relative_information_score
0.4423426579783694
kb_relative_information_score
0.5743466749594607
kb_relative_information_score
0.34966797041974906
kb_relative_information_score
0.417012520967162
kb_relative_information_score
0.3577422761316856
kb_relative_information_score
0.6064371134892711
kb_relative_information_score
0.27060280155016325
kb_relative_information_score
0.4598594529365819
kb_relative_information_score
0.32736108911228046
mean_absolute_error
0.26771439548246073
mean_absolute_error
0.2832890249061764
mean_absolute_error
0.22860739986347575
mean_absolute_error
0.3360640463262538
mean_absolute_error
0.2976092432039834
mean_absolute_error
0.32126051828278307
mean_absolute_error
0.2135255418505329
mean_absolute_error
0.3626323152361134
mean_absolute_error
0.28133938672669234
mean_absolute_error
0.33837566230685767
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
0.8518518518518519 [0.826087,0.870968]
precision
0.7955597643097643 [0.772727,0.8125]
precision
0.9084876543209878 [0.875,0.933333]
precision
0.8179337231968811 [0.842105,0.8]
precision
0.7851969616675499 [0.823529,0.756757]
precision
0.7402951824004455 [0.736842,0.742857]
precision
0.9259259259259259 [0.913043,0.935484]
precision
0.6871913580246913 [0.625,0.733333]
precision
0.8340852130325815 [0.842105,0.828571]
precision
0.7383442265795206 [0.7,0.764706]
predictive_accuracy
0.8518518518518519
predictive_accuracy
0.7962962962962963
predictive_accuracy
0.9074074074074074
predictive_accuracy
0.8148148148148148
predictive_accuracy
0.7777777777777777
predictive_accuracy
0.7407407407407408
predictive_accuracy
0.9259259259259259
predictive_accuracy
0.6851851851851852
predictive_accuracy
0.8333333333333333
predictive_accuracy
0.7407407407407408
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
0.5480112552091656
relative_absolute_error
0.5798925151037879
relative_absolute_error
0.46795925158792834
relative_absolute_error
0.6879229618042231
relative_absolute_error
0.6092059959500752
relative_absolute_error
0.657620146111378
relative_absolute_error
0.4370866945643719
relative_absolute_error
0.7423081971136208
relative_absolute_error
0.5793049930151133
relative_absolute_error
0.6967481978610592
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
0.3618792610564473
root_mean_squared_error
0.37441636486459345
root_mean_squared_error
0.29965925442087776
root_mean_squared_error
0.39884492558589796
root_mean_squared_error
0.3736270196327061
root_mean_squared_error
0.4256902401303302
root_mean_squared_error
0.28370406825672173
root_mean_squared_error
0.45849027778035584
root_mean_squared_error
0.3429848094771775
root_mean_squared_error
0.42840376503197763
root_relative_squared_error
0.7318167115166283
root_relative_squared_error
0.7571700905802297
root_relative_squared_error
0.6059912068616854
root_relative_squared_error
0.8065711778985792
root_relative_squared_error
0.7555738232778019
root_relative_squared_error
0.8608595882158299
root_relative_squared_error
0.5737255505314461
root_relative_squared_error
0.9271900422478978
root_relative_squared_error
0.6977137530960253
root_relative_squared_error
0.8714764924911875
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
0.8485273492286115 [0.826087,0.870968]
unweighted_recall
0.7889200561009817 [0.73913,0.83871]
unweighted_recall
0.9081346423562412 [0.913043,0.903226]
unweighted_recall
0.7994389901823282 [0.695652,0.903226]
unweighted_recall
0.755960729312763 [0.608696,0.903226]
unweighted_recall
0.723702664796634 [0.608696,0.83871]
unweighted_recall
0.9242636746143057 [0.913043,0.935484]
unweighted_recall
0.6809256661991585 [0.652174,0.709677]
unweighted_recall
0.8167613636363636 [0.727273,0.90625]
unweighted_recall
0.7244318181818181 [0.636364,0.8125]
usercpu_time_millis
315.0819999999612
usercpu_time_millis
283.09999999999036
usercpu_time_millis
290.82800000003317
usercpu_time_millis
269.35600000001614
usercpu_time_millis
291.84400000002597
usercpu_time_millis
282.10999999998876
usercpu_time_millis
298.48800000007714
usercpu_time_millis
279.137999999989
usercpu_time_millis
303.75600000002123
usercpu_time_millis
283.8419999999928
usercpu_time_millis_testing
8.735999999998967
usercpu_time_millis_testing
8.647999999993772
usercpu_time_millis_testing
8.64200000000892
usercpu_time_millis_testing
8.970000000033451
usercpu_time_millis_testing
10.120000000028995
usercpu_time_millis_testing
8.221999999989293
usercpu_time_millis_testing
8.634000000029118
usercpu_time_millis_testing
8.827999999994063
usercpu_time_millis_testing
8.350000000007185
usercpu_time_millis_testing
8.651999999983673
usercpu_time_millis_training
306.34599999996226
usercpu_time_millis_training
274.4519999999966
usercpu_time_millis_training
282.18600000002425
usercpu_time_millis_training
260.3859999999827
usercpu_time_millis_training
281.723999999997
usercpu_time_millis_training
273.88799999999947
usercpu_time_millis_training
289.854000000048
usercpu_time_millis_training
270.30999999999494
usercpu_time_millis_training
295.40600000001405
usercpu_time_millis_training
275.19000000000915
wall_clock_time_millis
159.13629531860352
wall_clock_time_millis
141.94011688232422
wall_clock_time_millis
145.60174942016602
wall_clock_time_millis
135.03694534301758
wall_clock_time_millis
147.05395698547363
wall_clock_time_millis
143.15128326416016
wall_clock_time_millis
150.98905563354492
wall_clock_time_millis
140.38801193237305
wall_clock_time_millis
152.76789665222168
wall_clock_time_millis
144.28997039794922
wall_clock_time_millis_testing
4.388093948364258
wall_clock_time_millis_testing
4.328012466430664
wall_clock_time_millis_testing
4.32586669921875
wall_clock_time_millis_testing
4.494905471801758
wall_clock_time_millis_testing
5.160093307495117
wall_clock_time_millis_testing
4.116296768188477
wall_clock_time_millis_testing
4.321098327636719
wall_clock_time_millis_testing
4.461050033569336
wall_clock_time_millis_testing
4.178047180175781
wall_clock_time_millis_testing
4.357099533081055
wall_clock_time_millis_training
154.74820137023926
wall_clock_time_millis_training
137.61210441589355
wall_clock_time_millis_training
141.27588272094727
wall_clock_time_millis_training
130.54203987121582
wall_clock_time_millis_training
141.89386367797852
wall_clock_time_millis_training
139.03498649597168
wall_clock_time_millis_training
146.6679573059082
wall_clock_time_millis_training
135.9269618988037
wall_clock_time_millis_training
148.5898494720459
wall_clock_time_millis_training
139.93287086486816
weighted_recall
0.8518518518518519 [0.826087,0.870968]
weighted_recall
0.7962962962962963 [0.73913,0.83871]
weighted_recall
0.9074074074074074 [0.913043,0.903226]
weighted_recall
0.8148148148148148 [0.695652,0.903226]
weighted_recall
0.7777777777777778 [0.608696,0.903226]
weighted_recall
0.7407407407407407 [0.608696,0.83871]
weighted_recall
0.9259259259259259 [0.913043,0.935484]
weighted_recall
0.6851851851851852 [0.652174,0.709677]
weighted_recall
0.8333333333333334 [0.727273,0.90625]
weighted_recall
0.7407407407407407 [0.636364,0.8125]