Run
10428200

Run 10428200

Task 43 (Supervised Classification) spambase Uploaded 08-12-2019 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"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)_C166.75510985968455
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.0
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree3
sklearn.svm.classes.SVC(31)_gamma0.7160996053142499
sklearn.svm.classes.SVC(31)_kernel"rbf"
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

0.9217 ± 0.0104
Per class
Cross-validation details (10-fold Crossvalidation)
0.809 ± 0.0159
Per class
Cross-validation details (10-fold Crossvalidation)
0.5971 ± 0.0328
Cross-validation details (10-fold Crossvalidation)
0.4964 ± 0.0216
Cross-validation details (10-fold Crossvalidation)
0.2502 ± 0.0102
Cross-validation details (10-fold Crossvalidation)
0.4776 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.8209 ± 0.0133
Cross-validation details (10-fold Crossvalidation)
4601
Per class
Cross-validation details (10-fold Crossvalidation)
0.8477 ± 0.0095
Per class
Cross-validation details (10-fold Crossvalidation)
0.8209 ± 0.0133
Cross-validation details (10-fold Crossvalidation)
0.9674 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.524 ± 0.0214
Cross-validation details (10-fold Crossvalidation)
0.4886 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
0.3477 ± 0.0103
Cross-validation details (10-fold Crossvalidation)
0.7115 ± 0.0212
Cross-validation details (10-fold Crossvalidation)
0.7779 ± 0.0175
Cross-validation details (10-fold Crossvalidation)