Run
10559711

Run 10559711

Task 31 (Supervised Classification) credit-g Uploaded 21-10-2020 by Cláudio Rebelo Sá
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  • openml-python random-subgroups random-subgroups_0.1.1 Sklearn_0.23.1.
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Flow

sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estima tor=randomsubgroups._randomsubgroups.RandomSubgroupClassifier)(1)Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit and transform methods. The final estimator only needs to implement fit. The transformers in the pipeline can be cached using ``memory`` argument. The purpose of the pipeline is to assemble several steps that can be cross-validated together while setting different parameters. For this, it enables setting parameters of the various steps using their names and the parameter name separated by a '__', as in the example below. A step's estimator may be replaced entirely by setting the parameter with its name to another estimator, or a transformer removed by setting it to 'passthrough' or ``None``.
sklearn.impute._base.SimpleImputer(16)_add_indicatorfalse
sklearn.impute._base.SimpleImputer(16)_copytrue
sklearn.impute._base.SimpleImputer(16)_fill_valuenull
sklearn.impute._base.SimpleImputer(16)_missing_valuesNaN
sklearn.impute._base.SimpleImputer(16)_strategy"mean"
sklearn.impute._base.SimpleImputer(16)_verbose0
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=randomsubgroups._randomsubgroups.RandomSubgroupClassifier)(1)_memorynull
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=randomsubgroups._randomsubgroups.RandomSubgroupClassifier)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimator", "step_name": "estimator"}}]
sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=randomsubgroups._randomsubgroups.RandomSubgroupClassifier)(1)_verbosefalse
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_bootstraptrue
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_intervals_onlytrue
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_depth1
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_features"auto"
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_samplesnull
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_bins5
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_estimators100
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_jobsnull
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_quality_function_weight0.5
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_result_set_size1
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_search_strategy"bestfirst"
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_verbose0

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

0.7218 ± 0.0413
Per class
Cross-validation details (10-fold Crossvalidation)
0.7154 ± 0.0476
Per class
Cross-validation details (10-fold Crossvalidation)
0.3659 ± 0.0819
Cross-validation details (10-fold Crossvalidation)
-1.2858 ± 0.0259
Cross-validation details (10-fold Crossvalidation)
0.4702 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
0.4202
Cross-validation details (10-fold Crossvalidation)
0.705 ± 0.0521
Cross-validation details (10-fold Crossvalidation)
1000
Per class
Cross-validation details (10-fold Crossvalidation)
0.7433 ± 0.0298
Per class
Cross-validation details (10-fold Crossvalidation)
0.705 ± 0.0521
Cross-validation details (10-fold Crossvalidation)
0.8813
Cross-validation details (10-fold Crossvalidation)
1.119 ± 0.0217
Cross-validation details (10-fold Crossvalidation)
0.4583
Cross-validation details (10-fold Crossvalidation)
0.6115 ± 0.0091
Cross-validation details (10-fold Crossvalidation)
1.3343 ± 0.0198
Cross-validation details (10-fold Crossvalidation)
0.7026 ± 0.0381
Cross-validation details (10-fold Crossvalidation)