Run
10382640

Run 10382640

Task 146822 (Supervised Classification) segment Uploaded 25-08-2019 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)_C0.5615070523152897
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.901112719190851
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.012492674428863062
sklearn.svm.classes.SVC(31)_kernel"sigmoid"
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.

17 Evaluation measures

0.8437 ± 0.0227
Per class
Cross-validation details (10-fold Crossvalidation)
0.7335 ± 0.0402
Per class
Cross-validation details (10-fold Crossvalidation)
0.6874 ± 0.0453
Cross-validation details (10-fold Crossvalidation)
0.7108 ± 0.0419
Cross-validation details (10-fold Crossvalidation)
0.0766 ± 0.0111
Cross-validation details (10-fold Crossvalidation)
0.2449
Cross-validation details (10-fold Crossvalidation)
2310
Per class
Cross-validation details (10-fold Crossvalidation)
0.7548 ± 0.0346
Per class
Cross-validation details (10-fold Crossvalidation)
0.732 ± 0.0389
Cross-validation details (10-fold Crossvalidation)
2.8074
Cross-validation details (10-fold Crossvalidation)
0.732 ± 0.0389
Per class
Cross-validation details (10-fold Crossvalidation)
0.3126 ± 0.0453
Cross-validation details (10-fold Crossvalidation)
0.3499
Cross-validation details (10-fold Crossvalidation)
0.2767 ± 0.02
Cross-validation details (10-fold Crossvalidation)
0.7907 ± 0.0572
Cross-validation details (10-fold Crossvalidation)