Run
10354582

Run 10354582

Task 146800 (Supervised Classification) MiceProtein Uploaded 21-08-2019 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)_C6.731333187866344
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef00.5722855162334912
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree4
sklearn.svm.classes.SVC(31)_gamma0.00026798359141741787
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_state17331
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

0.9079 ± 0.0151
Per class
Cross-validation details (10-fold Crossvalidation)
0.8398 ± 0.0266
Per class
Cross-validation details (10-fold Crossvalidation)
0.8165 ± 0.03
Cross-validation details (10-fold Crossvalidation)
0.8282 ± 0.0278
Cross-validation details (10-fold Crossvalidation)
0.04 ± 0.0066
Cross-validation details (10-fold Crossvalidation)
0.2185 ± 0
Cross-validation details (10-fold Crossvalidation)
1080
Per class
Cross-validation details (10-fold Crossvalidation)
0.8533 ± 0.0257
Per class
Cross-validation details (10-fold Crossvalidation)
0.8398 ± 0.0262
Cross-validation details (10-fold Crossvalidation)
2.993 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
0.8398 ± 0.0262
Per class
Cross-validation details (10-fold Crossvalidation)
0.1833 ± 0.03
Cross-validation details (10-fold Crossvalidation)
0.3305 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
0.2001 ± 0.0168
Cross-validation details (10-fold Crossvalidation)
0.6055 ± 0.0507
Cross-validation details (10-fold Crossvalidation)