Run
10436747

Run 10436747

Task 167119 (Supervised Classification) jungle_chess_2pcs_raw_endgame_complete Uploaded 31-01-2020 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"median"
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)_C690.6018801899403
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.6356144967116901
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.0008714226148272087
sklearn.svm.classes.SVC(31)_kernel"rbf"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilityfalse
sklearn.svm.classes.SVC(31)_random_state1
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.

18 Evaluation measures

0.7794 ± 0.0051
Per class
Cross-validation details (10-fold Crossvalidation)
0.7273 ± 0.0053
Per class
Cross-validation details (10-fold Crossvalidation)
0.5626 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
0.5392 ± 0.0082
Cross-validation details (10-fold Crossvalidation)
0.157 ± 0.0036
Cross-validation details (10-fold Crossvalidation)
0.3832 ± 0
Cross-validation details (10-fold Crossvalidation)
0.7645 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
44819
Per class
Cross-validation details (10-fold Crossvalidation)
0.736 ± 0.0179
Per class
Cross-validation details (10-fold Crossvalidation)
0.7645 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
1.3491 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.4097 ± 0.0093
Cross-validation details (10-fold Crossvalidation)
0.4377 ± 0
Cross-validation details (10-fold Crossvalidation)
0.3962 ± 0.0045
Cross-validation details (10-fold Crossvalidation)
0.9052 ± 0.0103
Cross-validation details (10-fold Crossvalidation)
0.5637 ± 0.0046
Cross-validation details (10-fold Crossvalidation)