Run
10320065

Run 10320065

Task 12 (Supervised Classification) mfeat-factors Uploaded 18-08-2019 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"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)_C7896.609635723991
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.5301251611609821
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree5
sklearn.svm.classes.SVC(31)_gamma0.004236570185569412
sklearn.svm.classes.SVC(31)_kernel"rbf"
sklearn.svm.classes.SVC(31)_max_iter-1
sklearn.svm.classes.SVC(31)_probabilityfalse
sklearn.svm.classes.SVC(31)_random_state30796
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

0.9892 ± 0.0033
Per class
Cross-validation details (10-fold Crossvalidation)
0.9805 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
0.9783 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
0.9796 ± 0.0063
Cross-validation details (10-fold Crossvalidation)
0.0039 ± 0.0012
Cross-validation details (10-fold Crossvalidation)
0.18
Cross-validation details (10-fold Crossvalidation)
2000
Per class
Cross-validation details (10-fold Crossvalidation)
0.9805 ± 0.0058
Per class
Cross-validation details (10-fold Crossvalidation)
0.9805 ± 0.006
Cross-validation details (10-fold Crossvalidation)
3.3219
Cross-validation details (10-fold Crossvalidation)
0.9805 ± 0.006
Per class
Cross-validation details (10-fold Crossvalidation)
0.0217 ± 0.0067
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)
0.0624 ± 0.0097
Cross-validation details (10-fold Crossvalidation)
0.2082 ± 0.0324
Cross-validation details (10-fold Crossvalidation)