Run
10455218

Run 10455218

Task 9914 (Supervised Classification) wilt Uploaded 19-05-2020 by Marc Zöller
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  • automl_meta_features openml-python Sklearn_0.22.1.
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Flow

sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.RobustScaler,s tep_1=sklearn.naive_bayes.BernoulliNB)(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.naive_bayes.BernoulliNB(11)_alpha81.59519596496565
sklearn.naive_bayes.BernoulliNB(11)_binarize0.0
sklearn.naive_bayes.BernoulliNB(11)_class_priornull
sklearn.naive_bayes.BernoulliNB(11)_fit_priorfalse
sklearn.preprocessing._data.RobustScaler(1)_copyfalse
sklearn.preprocessing._data.RobustScaler(1)_quantile_range[24.275836142495244, 92.52607450557818]
sklearn.preprocessing._data.RobustScaler(1)_with_centeringfalse
sklearn.preprocessing._data.RobustScaler(1)_with_scalingtrue
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.RobustScaler,step_1=sklearn.naive_bayes.BernoulliNB)(1)_memorynull
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.RobustScaler,step_1=sklearn.naive_bayes.BernoulliNB)(1)_steps[{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "step_1", "step_name": "step_1"}}]
sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._data.RobustScaler,step_1=sklearn.naive_bayes.BernoulliNB)(1)_verbosefalse

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

0.4969 ± 0.0012
Per class
Cross-validation details (10-fold Crossvalidation)
0.9191 ± 0.0012
Per class
Cross-validation details (10-fold Crossvalidation)
-0.0028 ± 0.004
Cross-validation details (10-fold Crossvalidation)
-6.6702 ± 0.0701
Cross-validation details (10-fold Crossvalidation)
0.2864 ± 0.0014
Cross-validation details (10-fold Crossvalidation)
0.1022 ± 0.0006
Cross-validation details (10-fold Crossvalidation)
0.9446 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
4839
Per class
Cross-validation details (10-fold Crossvalidation)
0.895 ± 0.0019
Per class
Cross-validation details (10-fold Crossvalidation)
0.9446 ± 0.0023
Cross-validation details (10-fold Crossvalidation)
0.3029 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
2.8021 ± 0.0181
Cross-validation details (10-fold Crossvalidation)
0.2259 ± 0.0013
Cross-validation details (10-fold Crossvalidation)
0.3073 ± 0.0027
Cross-validation details (10-fold Crossvalidation)
1.3602 ± 0.0123
Cross-validation details (10-fold Crossvalidation)
0.4992 ± 0.0012
Cross-validation details (10-fold Crossvalidation)