| Issue | #Downvotes for this reason | By |
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| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,gaussi annb=sklearn.naive_bayes.GaussianNB)(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 to None. |
| sklearn.impute.SimpleImputer(16)_copy | true |
| sklearn.impute.SimpleImputer(16)_fill_value | null |
| sklearn.impute.SimpleImputer(16)_missing_values | NaN |
| sklearn.impute.SimpleImputer(16)_strategy | "mean" |
| sklearn.impute.SimpleImputer(16)_verbose | 0 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,gaussiannb=sklearn.naive_bayes.GaussianNB)(1)_memory | null |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,gaussiannb=sklearn.naive_bayes.GaussianNB)(1)_steps | [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gaussiannb", "step_name": "gaussiannb"}}] |
| sklearn.naive_bayes.GaussianNB(17)_priors | null |
| sklearn.naive_bayes.GaussianNB(17)_var_smoothing | 1e-09 |
0.6177 ± 0.0099 Per class Cross-validation details (10 times 10-fold Crossvalidation)
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0.798 ± 0.004 Per class Cross-validation details (10 times 10-fold Crossvalidation)
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0.1204 ± 0.0137 Cross-validation details (10 times 10-fold Crossvalidation)
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-0.5546 ± 0.0317 Cross-validation details (10 times 10-fold Crossvalidation)
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0.2444 ± 0.0043 Cross-validation details (10 times 10-fold Crossvalidation)
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0.2157 ± 0 Cross-validation details (10 times 10-fold Crossvalidation)
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0.7869 ± 0.0054 Cross-validation details (10 times 10-fold Crossvalidation)
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729830 Per class Cross-validation details (10 times 10-fold Crossvalidation) |
0.8108 ± 0.003 Per class Cross-validation details (10 times 10-fold Crossvalidation)
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0.7869 ± 0.0054 Cross-validation details (10 times 10-fold Crossvalidation)
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0.5379 ± 0.0002 Cross-validation details (10 times 10-fold Crossvalidation)
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1.133 ± 0.0199 Cross-validation details (10 times 10-fold Crossvalidation)
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0.3284 ± 0.0001 Cross-validation details (10 times 10-fold Crossvalidation)
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0.4043 ± 0.0048 Cross-validation details (10 times 10-fold Crossvalidation)
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1.2309 ± 0.0145 Cross-validation details (10 times 10-fold Crossvalidation)
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0.5676 ± 0.0075 Cross-validation details (10 times 10-fold Crossvalidation)
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