OpenML
10350465

Run 10350465

Task 53 (Supervised Classification) vehicle Uploaded 21-08-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.cl asses.SVC)(1)Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(1)_copytrue
sklearn.impute._base.SimpleImputer(1)_fill_valuenull
sklearn.impute._base.SimpleImputer(1)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(1)_strategy"most_frequent"
sklearn.impute._base.SimpleImputer(1)_verbose0
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue
sklearn.svm.classes.SVC(31)_C3.081620245614723
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.053322514098660845
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.31447231452702795
sklearn.svm.classes.SVC(31)_kernel"poly"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilityfalse
sklearn.svm.classes.SVC(31)_random_state48442
sklearn.svm.classes.SVC(31)_shrinkingtrue
sklearn.svm.classes.SVC(31)_tol0.001
sklearn.svm.classes.SVC(31)_verbosefalse
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_verbosefalse

Result files

xml
Description

XML file describing the run, including user-defined evaluation measures.

arff
Predictions

ARFF file with instance-level predictions generated by the model.

17 Evaluation measures

0.7294 ± 0.0483
Per class
Cross-validation details (10-fold Crossvalidation)
0.5934 ± 0.0766
Per class
Cross-validation details (10-fold Crossvalidation)
0.4584 ± 0.0972
Cross-validation details (10-fold Crossvalidation)
0.5094 ± 0.0888
Cross-validation details (10-fold Crossvalidation)
0.2033 ± 0.0366
Cross-validation details (10-fold Crossvalidation)
0.3748 ± 0
Cross-validation details (10-fold Crossvalidation)
846
Per class
Cross-validation details (10-fold Crossvalidation)
0.6191 ± 0.0812
Per class
Cross-validation details (10-fold Crossvalidation)
0.5934 ± 0.0733
Cross-validation details (10-fold Crossvalidation)
1.9991 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.5934 ± 0.0733
Per class
Cross-validation details (10-fold Crossvalidation)
0.5424 ± 0.0977
Cross-validation details (10-fold Crossvalidation)
0.4329 ± 0
Cross-validation details (10-fold Crossvalidation)
0.4509 ± 0.0413
Cross-validation details (10-fold Crossvalidation)
1.0415 ± 0.0953
Cross-validation details (10-fold Crossvalidation)