| 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 | 2.769084474487514e-07 |
| 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 | 24.130669866500526 |
| sklearn.svm._classes.SVC(4)_decision_function_shape | "ovo" |
| sklearn.svm._classes.SVC(4)_degree | 2 |
| sklearn.svm._classes.SVC(4)_gamma | 0.025562696792769995 |
| 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 | 1.6421833254633989e-07 |
| sklearn.svm._classes.SVC(4)_verbose | false |
0.7942 ± 0.027 Per class Cross-validation details (10-fold Crossvalidation)
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0.6664 ± 0.0447 Per class Cross-validation details (10-fold Crossvalidation)
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0.5888 ± 0.054 Cross-validation details (10-fold Crossvalidation)
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0.6287 ± 0.0484 Cross-validation details (10-fold Crossvalidation)
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0.1543 ± 0.0202 Cross-validation details (10-fold Crossvalidation)
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0.3748 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.6915 ± 0.0403 Cross-validation details (10-fold Crossvalidation)
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846 Per class Cross-validation details (10-fold Crossvalidation) |
0.6769 ± 0.0524 Per class Cross-validation details (10-fold Crossvalidation)
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0.6915 ± 0.0403 Cross-validation details (10-fold Crossvalidation)
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1.9991 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.4115 ± 0.0537 Cross-validation details (10-fold Crossvalidation)
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0.4329 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.3928 ± 0.0251 Cross-validation details (10-fold Crossvalidation)
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0.9072 ± 0.0579 Cross-validation details (10-fold Crossvalidation)
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0.6944 ± 0.0416 Cross-validation details (10-fold Crossvalidation)
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