Run
10357317

Run 10357317

Task 11 (Supervised Classification) balance-scale Uploaded 21-08-2019 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"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)_C81356.92108932823
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.33706310267468553
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree2
sklearn.svm.classes.SVC(31)_gamma2.238549391298506
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_state59518
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

0.291 ± 0.0345
Per class
Cross-validation details (10-fold Crossvalidation)
0.196 ± 0.045
Per class
Cross-validation details (10-fold Crossvalidation)
-0.383 ± 0.0777
Cross-validation details (10-fold Crossvalidation)
-0.2726 ± 0.0795
Cross-validation details (10-fold Crossvalidation)
0.5248 ± 0.03
Cross-validation details (10-fold Crossvalidation)
0.3798 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
625
Per class
Cross-validation details (10-fold Crossvalidation)
0.1874 ± 0.0538
Per class
Cross-validation details (10-fold Crossvalidation)
0.2128 ± 0.045
Cross-validation details (10-fold Crossvalidation)
1.3181 ± 0.0124
Cross-validation details (10-fold Crossvalidation)
0.2128 ± 0.045
Per class
Cross-validation details (10-fold Crossvalidation)
1.3819 ± 0.0776
Cross-validation details (10-fold Crossvalidation)
0.4356 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.7244 ± 0.0205
Cross-validation details (10-fold Crossvalidation)
1.6632 ± 0.0456
Cross-validation details (10-fold Crossvalidation)