Run
10229052

Run 10229052

Task 45 (Supervised Classification) splice Uploaded 05-07-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklea rn_extra.fast_kernel.FKC_EigenPro)(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_extra.fast_kernel.FKC_EigenPro(1)_bandwidth9
sklearn_extra.fast_kernel.FKC_EigenPro(1)_batch_size"auto"
sklearn_extra.fast_kernel.FKC_EigenPro(1)_coef01
sklearn_extra.fast_kernel.FKC_EigenPro(1)_degree4
sklearn_extra.fast_kernel.FKC_EigenPro(1)_gammanull
sklearn_extra.fast_kernel.FKC_EigenPro(1)_kernel"cauchy"
sklearn_extra.fast_kernel.FKC_EigenPro(1)_kernel_paramsnull
sklearn_extra.fast_kernel.FKC_EigenPro(1)_n_components500
sklearn_extra.fast_kernel.FKC_EigenPro(1)_n_epoch2
sklearn_extra.fast_kernel.FKC_EigenPro(1)_random_state60825
sklearn_extra.fast_kernel.FKC_EigenPro(1)_subsample_size"auto"
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(1)_memorynull
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(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": "fkc_eigenpro", "step_name": "fkc_eigenpro"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(1)_verbosefalse
sklearn.preprocessing.data.StandardScaler(29)_copytrue
sklearn.preprocessing.data.StandardScaler(29)_with_meantrue
sklearn.preprocessing.data.StandardScaler(29)_with_stdtrue

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

0.9429 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
0.9252 ± 0.0145
Per class
Cross-validation details (10-fold Crossvalidation)
0.8789 ± 0.0232
Cross-validation details (10-fold Crossvalidation)
0.8858 ± 0.0223
Cross-validation details (10-fold Crossvalidation)
0.0499 ± 0.0096
Cross-validation details (10-fold Crossvalidation)
0.4101 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
3190
Per class
Cross-validation details (10-fold Crossvalidation)
0.9259 ± 0.014
Per class
Cross-validation details (10-fold Crossvalidation)
0.9251 ± 0.0144
Cross-validation details (10-fold Crossvalidation)
1.4802 ± 0.0018
Cross-validation details (10-fold Crossvalidation)
0.9251 ± 0.0144
Per class
Cross-validation details (10-fold Crossvalidation)
0.1218 ± 0.0233
Cross-validation details (10-fold Crossvalidation)
0.4528 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
0.2235 ± 0.0215
Cross-validation details (10-fold Crossvalidation)
0.4936 ± 0.0473
Cross-validation details (10-fold Crossvalidation)