| 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 | 1.1318722174364994e-05 |
| sklearn.svm._classes.SVC(4)_break_ties | false |
| sklearn.svm._classes.SVC(4)_cache_size | 200 |
| sklearn.svm._classes.SVC(4)_class_weight | null |
| sklearn.svm._classes.SVC(4)_coef0 | -28.793097998926992 |
| sklearn.svm._classes.SVC(4)_decision_function_shape | "ovr" |
| sklearn.svm._classes.SVC(4)_degree | 5 |
| sklearn.svm._classes.SVC(4)_gamma | 6.151199506271602e-06 |
| sklearn.svm._classes.SVC(4)_kernel | "poly" |
| 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 | 0.0857091298292338 |
| sklearn.svm._classes.SVC(4)_verbose | false |
0.6608 ± 0.0318 Per class Cross-validation details (10-fold Crossvalidation)
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0.4707 ± 0.0482 Per class Cross-validation details (10-fold Crossvalidation)
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0.3223 ± 0.064 Cross-validation details (10-fold Crossvalidation)
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0.3872 ± 0.059 Cross-validation details (10-fold Crossvalidation)
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0.2547 ± 0.0242 Cross-validation details (10-fold Crossvalidation)
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0.3748 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.4905 ± 0.0484 Cross-validation details (10-fold Crossvalidation)
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846 Per class Cross-validation details (10-fold Crossvalidation) |
0.5079 ± 0.0638 Per class Cross-validation details (10-fold Crossvalidation)
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0.4905 ± 0.0484 Cross-validation details (10-fold Crossvalidation)
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1.9991 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.6796 ± 0.0646 Cross-validation details (10-fold Crossvalidation)
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0.4329 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.5047 ± 0.0235 Cross-validation details (10-fold Crossvalidation)
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1.1658 ± 0.0543 Cross-validation details (10-fold Crossvalidation)
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0.496 ± 0.0493 Cross-validation details (10-fold Crossvalidation)
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