Run
10559724

Run 10559724

Task 4537 (Supervised Classification) iris Uploaded 22-10-2020 by Claudio Rebelo Sá
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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_onlyfalse
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_depth3
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_features"auto"
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_max_samplesnull
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_bins20
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_estimators300
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_n_jobs3
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_quality_function_weight0.5
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_result_set_size20
randomsubgroups._randomsubgroups.RandomSubgroupClassifier(1)_search_strategy"bestfirst2"
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

0.9999
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
0.992 ± 0.0232
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
0.9821 ± 0.0502
Cross-validation details (10 times 10-fold Crossvalidation)
-0.3631 ± 0.0565
Cross-validation details (10 times 10-fold Crossvalidation)
0.2808 ± 0.0128
Cross-validation details (10 times 10-fold Crossvalidation)
0.4452 ± 0
Cross-validation details (10 times 10-fold Crossvalidation)
0.992 ± 0.0237
Cross-validation details (10 times 10-fold Crossvalidation)
1500
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
0.9922 ± 0.019
Per class
Cross-validation details (10 times 10-fold Crossvalidation)
0.992 ± 0.0237
Cross-validation details (10 times 10-fold Crossvalidation)
0.9183 ± 0
Cross-validation details (10 times 10-fold Crossvalidation)
0.6307 ± 0.0288
Cross-validation details (10 times 10-fold Crossvalidation)
0.4714 ± 0
Cross-validation details (10 times 10-fold Crossvalidation)
0.3925 ± 0.0158
Cross-validation details (10 times 10-fold Crossvalidation)
0.8327 ± 0.0336
Cross-validation details (10 times 10-fold Crossvalidation)
0.994 ± 0.0178
Cross-validation details (10 times 10-fold Crossvalidation)