| Issue | #Downvotes for this reason | By |
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| sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBin sDiscretizer,step_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)_alpha | 76.51241531671488 |
| sklearn.naive_bayes.BernoulliNB(11)_binarize | 0.0 |
| sklearn.naive_bayes.BernoulliNB(11)_class_prior | null |
| sklearn.naive_bayes.BernoulliNB(11)_fit_prior | false |
| sklearn.preprocessing._discretization.KBinsDiscretizer(1)_encode | "onehot-dense" |
| sklearn.preprocessing._discretization.KBinsDiscretizer(1)_n_bins | 43 |
| sklearn.preprocessing._discretization.KBinsDiscretizer(1)_strategy | "quantile" |
| sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,step_1=sklearn.naive_bayes.BernoulliNB)(1)_memory | null |
| sklearn.pipeline.Pipeline(step_0=sklearn.preprocessing._discretization.KBinsDiscretizer,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._discretization.KBinsDiscretizer,step_1=sklearn.naive_bayes.BernoulliNB)(1)_verbose | false |
0.9551 ± 0.0111 Per class Cross-validation details (10-fold Crossvalidation)
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0.7033 ± 0.0458 Per class Cross-validation details (10-fold Crossvalidation)
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0.6479 ± 0.0533 Cross-validation details (10-fold Crossvalidation)
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0.5995 ± 0.0244 Cross-validation details (10-fold Crossvalidation)
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0.1095 ± 0.005 Cross-validation details (10-fold Crossvalidation)
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0.1975 Cross-validation details (10-fold Crossvalidation)
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0.687 ± 0.0474 Cross-validation details (10-fold Crossvalidation)
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1080 Per class Cross-validation details (10-fold Crossvalidation) |
0.7879 ± 0.0293 Per class Cross-validation details (10-fold Crossvalidation)
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0.687 ± 0.0474 Cross-validation details (10-fold Crossvalidation)
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3.1699 Cross-validation details (10-fold Crossvalidation)
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0.5542 ± 0.0254 Cross-validation details (10-fold Crossvalidation)
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0.3143 Cross-validation details (10-fold Crossvalidation)
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0.2187 ± 0.0083 Cross-validation details (10-fold Crossvalidation)
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0.6959 ± 0.0264 Cross-validation details (10-fold Crossvalidation)
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0.687 ± 0.0474 Cross-validation details (10-fold Crossvalidation)
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