Run
10435949

Run 10435949

Task 9985 (Supervised Classification) first-order-theorem-proving Uploaded 16-01-2020 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)_C149.07622270551335
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.0
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree3
sklearn.svm.classes.SVC(31)_gamma0.05610768111553853
sklearn.svm.classes.SVC(31)_kernel"rbf"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilitytrue
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

0.8283 ± 0.0109
Per class
Cross-validation details (10-fold Crossvalidation)
0.5586 ± 0.0158
Per class
Cross-validation details (10-fold Crossvalidation)
0.4168 ± 0.0213
Cross-validation details (10-fold Crossvalidation)
0.3057 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
0.2019 ± 0.0011
Cross-validation details (10-fold Crossvalidation)
0.2508 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.5837 ± 0.0142
Cross-validation details (10-fold Crossvalidation)
6118
Per class
Cross-validation details (10-fold Crossvalidation)
0.5593 ± 0.0171
Per class
Cross-validation details (10-fold Crossvalidation)
0.5837 ± 0.0142
Cross-validation details (10-fold Crossvalidation)
2.3 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
0.805 ± 0.0043
Cross-validation details (10-fold Crossvalidation)
0.3541 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.3092 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
0.8732 ± 0.0073
Cross-validation details (10-fold Crossvalidation)
0.4339 ± 0.0178
Cross-validation details (10-fold Crossvalidation)