Run
10229088

Run 10229088

Task 9952 (Supervised Classification) phoneme Uploaded 06-07-2019 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)_bandwidth4
sklearn_extra.fast_kernel.FKC_EigenPro(1)_batch_size"auto"
sklearn_extra.fast_kernel.FKC_EigenPro(1)_coef00.1
sklearn_extra.fast_kernel.FKC_EigenPro(1)_degree3
sklearn_extra.fast_kernel.FKC_EigenPro(1)_gammanull
sklearn_extra.fast_kernel.FKC_EigenPro(1)_kernel"rbf"
sklearn_extra.fast_kernel.FKC_EigenPro(1)_kernel_paramsnull
sklearn_extra.fast_kernel.FKC_EigenPro(1)_n_components2000
sklearn_extra.fast_kernel.FKC_EigenPro(1)_n_epoch2
sklearn_extra.fast_kernel.FKC_EigenPro(1)_random_state21710
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

Area under ROC curve
0.8245 ± 0.0167
Per class
Cross-validation details (10-fold Crossvalidation)
F measure
0.8576 ± 0.012
Per class
Cross-validation details (10-fold Crossvalidation)
Kappa
0.655 ± 0.0293
Cross-validation details (10-fold Crossvalidation)
KB relative information score
0.6316 ± 0.0312
Cross-validation details (10-fold Crossvalidation)
Mean absolute error
0.1417 ± 0.0119
Cross-validation details (10-fold Crossvalidation)
Mean prior absolute error
0.4147 ± 0.0003
Cross-validation details (10-fold Crossvalidation)
Number of instances
5404
Per class
Cross-validation details (10-fold Crossvalidation)
Precision
0.8571 ± 0.0121
Per class
Cross-validation details (10-fold Crossvalidation)
Predictive accuracy
0.8583 ± 0.0119
Cross-validation details (10-fold Crossvalidation)
Prior entropy
0.8732 ± 0.001
Cross-validation details (10-fold Crossvalidation)
Recall
0.8583 ± 0.0119
Per class
Cross-validation details (10-fold Crossvalidation)
Relative absolute error
0.3418 ± 0.0289
Cross-validation details (10-fold Crossvalidation)
Root mean prior squared error
0.4554 ± 0.0004
Cross-validation details (10-fold Crossvalidation)
Root mean squared error
0.3765 ± 0.0158
Cross-validation details (10-fold Crossvalidation)
Root relative squared error
0.8268 ± 0.0348
Cross-validation details (10-fold Crossvalidation)