Run
10429850

Run 10429850

Task 14 (Supervised Classification) mfeat-fourier Uploaded 09-12-2019 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)_C0.4212172063086123
sklearn.svm.classes.SVC(31)_cache_size200
sklearn.svm.classes.SVC(31)_class_weightnull
sklearn.svm.classes.SVC(31)_coef0-0.30890982063706174
sklearn.svm.classes.SVC(31)_decision_function_shape"ovr"
sklearn.svm.classes.SVC(31)_degree3
sklearn.svm.classes.SVC(31)_gamma0.012608109887061762
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

0.944 ± 0.0073
Per class
Cross-validation details (10-fold Crossvalidation)
0.6984 ± 0.0334
Per class
Cross-validation details (10-fold Crossvalidation)
0.665 ± 0.037
Cross-validation details (10-fold Crossvalidation)
0.6124 ± 0.0187
Cross-validation details (10-fold Crossvalidation)
0.1033 ± 0.0042
Cross-validation details (10-fold Crossvalidation)
0.18
Cross-validation details (10-fold Crossvalidation)
0.6985 ± 0.0333
Cross-validation details (10-fold Crossvalidation)
2000
Per class
Cross-validation details (10-fold Crossvalidation)
0.7048 ± 0.0343
Per class
Cross-validation details (10-fold Crossvalidation)
0.6985 ± 0.0333
Cross-validation details (10-fold Crossvalidation)
3.3219
Cross-validation details (10-fold Crossvalidation)
0.5739 ± 0.0231
Cross-validation details (10-fold Crossvalidation)
0.3
Cross-validation details (10-fold Crossvalidation)
0.2131 ± 0.0054
Cross-validation details (10-fold Crossvalidation)
0.7102 ± 0.018
Cross-validation details (10-fold Crossvalidation)
0.6985 ± 0.0333
Cross-validation details (10-fold Crossvalidation)