Run
10309560

Run 10309560

Task 14965 (Supervised Classification) bank-marketing Uploaded 03-08-2019 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,fkceigenpro=sklear n_extra.fast_kernel.FKCEigenPro)(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.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(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": "fkceigenpro", "step_name": "fkceigenpro"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(1)_verbosefalse
sklearn_extra.fast_kernel.FKCEigenPro(1)_bandwidth5
sklearn_extra.fast_kernel.FKCEigenPro(1)_batch_size"auto"
sklearn_extra.fast_kernel.FKCEigenPro(1)_coef01
sklearn_extra.fast_kernel.FKCEigenPro(1)_degree2
sklearn_extra.fast_kernel.FKCEigenPro(1)_gamma0.01
sklearn_extra.fast_kernel.FKCEigenPro(1)_kernel"rbf"
sklearn_extra.fast_kernel.FKCEigenPro(1)_kernel_params"null"
sklearn_extra.fast_kernel.FKCEigenPro(1)_n_components1000
sklearn_extra.fast_kernel.FKCEigenPro(1)_n_epoch2
sklearn_extra.fast_kernel.FKCEigenPro(1)_random_state33036
sklearn_extra.fast_kernel.FKCEigenPro(1)_subsample_size"auto"

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

Area under ROC curve
0.6503 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8847 ± 0.0045
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.3816 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.3672 ± 0.0233
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1006 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.2066 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Number of instances
45211
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8834 ± 0.0054
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8994 ± 0.0037
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.5206 ± 0.0002
Cross-validation details (10-fold Crossvalidation)
Recall
0.8994 ± 0.0037
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.4869 ± 0.0179
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.3214 ± 0.0001
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3172 ± 0.0058
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.9868 ± 0.0181
Cross-validation details (10-fold Crossvalidation)