OpenML
10336849

Run 10336849

Task 3549 (Supervised Classification) analcatdata_authorship Uploaded 20-08-2019 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)_C1.2657047182391707
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.8221820150304964
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree3
sklearn.svm.classes.SVC(31)_gamma0.08578255665114355
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_state5502
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

0.9835 ± 0.0104
Per class
Cross-validation details (10-fold Crossvalidation)
0.9773 ± 0.0145
Per class
Cross-validation details (10-fold Crossvalidation)
0.9671 ± 0.0207
Cross-validation details (10-fold Crossvalidation)
0.9666 ± 0.0232
Cross-validation details (10-fold Crossvalidation)
0.0113 ± 0.0071
Cross-validation details (10-fold Crossvalidation)
0.3439 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
841
Per class
Cross-validation details (10-fold Crossvalidation)
0.9777 ± 0.0135
Per class
Cross-validation details (10-fold Crossvalidation)
0.9774 ± 0.0143
Cross-validation details (10-fold Crossvalidation)
1.7874 ± 0.0186
Cross-validation details (10-fold Crossvalidation)
0.9774 ± 0.0143
Per class
Cross-validation details (10-fold Crossvalidation)
0.0328 ± 0.0207
Cross-validation details (10-fold Crossvalidation)
0.4146 ± 0.0015
Cross-validation details (10-fold Crossvalidation)
0.1063 ± 0.0434
Cross-validation details (10-fold Crossvalidation)
0.2564 ± 0.1045
Cross-validation details (10-fold Crossvalidation)