Run
10436366

Run 10436366

Task 9985 (Supervised Classification) first-order-theorem-proving Uploaded 23-01-2020 by Heinrich Peters
0 likes downloaded by 0 people 0 issues 0 downvotes , 0 total downloads
Issue #Downvotes for this reason By


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)_C8.730007255107827
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.7936588323982094
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree1
sklearn.svm.classes.SVC(31)_gamma0.17297728205561683
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_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

0.6012 ± 0.014
Per class
Cross-validation details (10-fold Crossvalidation)
0.4141 ± 0.0217
Per class
Cross-validation details (10-fold Crossvalidation)
0.2142 ± 0.0282
Cross-validation details (10-fold Crossvalidation)
0.2879 ± 0.0199
Cross-validation details (10-fold Crossvalidation)
0.1728 ± 0.0052
Cross-validation details (10-fold Crossvalidation)
0.2508 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.4817 ± 0.0157
Cross-validation details (10-fold Crossvalidation)
6118
Per class
Cross-validation details (10-fold Crossvalidation)
0.439 ± 0.0352
Per class
Cross-validation details (10-fold Crossvalidation)
0.4817 ± 0.0157
Cross-validation details (10-fold Crossvalidation)
2.3 ± 0.0025
Cross-validation details (10-fold Crossvalidation)
0.689 ± 0.0209
Cross-validation details (10-fold Crossvalidation)
0.3541 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.4157 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
1.1739 ± 0.0178
Cross-validation details (10-fold Crossvalidation)
0.2907 ± 0.0198
Cross-validation details (10-fold Crossvalidation)