Run
10434091

Run 10434091

Task 9952 (Supervised Classification) phoneme Uploaded 17-12-2019 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)_C170.5572031055097
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.7430320055311159
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree2
sklearn.svm.classes.SVC(31)_gamma0.049727598083142026
sklearn.svm.classes.SVC(31)_kernel"poly"
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

0.8812 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
0.8124 ± 0.0135
Per class
Cross-validation details (10-fold Crossvalidation)
0.5431 ± 0.033
Cross-validation details (10-fold Crossvalidation)
0.3791 ± 0.0216
Cross-validation details (10-fold Crossvalidation)
0.2556 ± 0.0075
Cross-validation details (10-fold Crossvalidation)
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.8144 ± 0.0134
Cross-validation details (10-fold Crossvalidation)
5404
Per class
Cross-validation details (10-fold Crossvalidation)
0.8111 ± 0.0138
Per class
Cross-validation details (10-fold Crossvalidation)
0.8144 ± 0.0134
Cross-validation details (10-fold Crossvalidation)
0.8732 ± 0.001
Cross-validation details (10-fold Crossvalidation)
0.6162 ± 0.0181
Cross-validation details (10-fold Crossvalidation)
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
0.3546 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
0.7788 ± 0.0198
Cross-validation details (10-fold Crossvalidation)
0.766 ± 0.0183
Cross-validation details (10-fold Crossvalidation)