| 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 | 25.06417769564646 |
| 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" |
| sklearn.preprocessing._discretization.KBinsDiscretizer(1)_n_bins | 24 |
| sklearn.preprocessing._discretization.KBinsDiscretizer(1)_strategy | "uniform" |
| 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 |
0.5672 ± 0.0063 Per class Cross-validation details (10-fold Crossvalidation)
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0.5205 ± 0.009 Per class Cross-validation details (10-fold Crossvalidation)
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0.096 ± 0.0139 Cross-validation details (10-fold Crossvalidation)
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0.0517 ± 0.0063 Cross-validation details (10-fold Crossvalidation)
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0.4718 ± 0.0029 Cross-validation details (10-fold Crossvalidation)
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0.4948 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.5804 ± 0.0075 Cross-validation details (10-fold Crossvalidation)
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14980 Per class Cross-validation details (10-fold Crossvalidation) |
0.5862 ± 0.016 Per class Cross-validation details (10-fold Crossvalidation)
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0.5804 ± 0.0075 Cross-validation details (10-fold Crossvalidation)
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0.9924 ± 0.0001 Cross-validation details (10-fold Crossvalidation)
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0.9535 ± 0.0058 Cross-validation details (10-fold Crossvalidation)
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0.4974 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.4936 ± 0.0036 Cross-validation details (10-fold Crossvalidation)
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0.9924 ± 0.0072 Cross-validation details (10-fold Crossvalidation)
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0.545 ± 0.0065 Cross-validation details (10-fold Crossvalidation)
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