| Issue | #Downvotes for this reason | By |
|---|
| sklearn.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(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.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_memory | null |
| sklearn.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_steps | [{"oml-python:serialized_object": "component_reference", "value": {"key": "step_0", "step_name": "step_0"}}] |
| sklearn.pipeline.Pipeline(step_0=sklearn.svm._classes.SVC)(1)_verbose | false |
| sklearn.svm._classes.SVC(4)_C | 3.9290085973483785e-07 |
| sklearn.svm._classes.SVC(4)_break_ties | true |
| sklearn.svm._classes.SVC(4)_cache_size | 200 |
| sklearn.svm._classes.SVC(4)_class_weight | null |
| sklearn.svm._classes.SVC(4)_coef0 | 0.0 |
| sklearn.svm._classes.SVC(4)_decision_function_shape | "ovr" |
| sklearn.svm._classes.SVC(4)_degree | 3 |
| sklearn.svm._classes.SVC(4)_gamma | "scale" |
| sklearn.svm._classes.SVC(4)_kernel | "linear" |
| sklearn.svm._classes.SVC(4)_max_iter | -1 |
| sklearn.svm._classes.SVC(4)_probability | false |
| sklearn.svm._classes.SVC(4)_random_state | 42 |
| sklearn.svm._classes.SVC(4)_shrinking | true |
| sklearn.svm._classes.SVC(4)_tol | 1.720541868419142e-05 |
| sklearn.svm._classes.SVC(4)_verbose | false |
0.8788 ± 0.0579 Per class Cross-validation details (10-fold Crossvalidation)
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0.9041 ± 0.0488 Per class Cross-validation details (10-fold Crossvalidation)
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0.7918 ± 0.1055 Cross-validation details (10-fold Crossvalidation)
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0.795 ± 0.0975 Cross-validation details (10-fold Crossvalidation)
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0.0931 ± 0.0445 Cross-validation details (10-fold Crossvalidation)
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0.4676 ± 0.0019 Cross-validation details (10-fold Crossvalidation)
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0.9069 ± 0.0445 Cross-validation details (10-fold Crossvalidation)
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569 Per class Cross-validation details (10-fold Crossvalidation) |
0.9146 ± 0.0365 Per class Cross-validation details (10-fold Crossvalidation)
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0.9069 ± 0.0445 Cross-validation details (10-fold Crossvalidation)
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0.9526 ± 0.0055 Cross-validation details (10-fold Crossvalidation)
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0.1992 ± 0.0949 Cross-validation details (10-fold Crossvalidation)
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0.4835 ± 0.0019 Cross-validation details (10-fold Crossvalidation)
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0.3052 ± 0.0712 Cross-validation details (10-fold Crossvalidation)
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0.6312 ± 0.1463 Cross-validation details (10-fold Crossvalidation)
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0.8788 ± 0.0579 Cross-validation details (10-fold Crossvalidation)
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