| Issue | #Downvotes for this reason | By |
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| 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 | 1.7315458284351388 |
| 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 | -10.227513806899573 |
| sklearn.svm._classes.SVC(4)_decision_function_shape | "ovr" |
| sklearn.svm._classes.SVC(4)_degree | 5 |
| sklearn.svm._classes.SVC(4)_gamma | 1.0411928509906779e-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 | false |
| sklearn.svm._classes.SVC(4)_tol | 0.003929227644907825 |
| sklearn.svm._classes.SVC(4)_verbose | false |
0.6663 ± 0.025 Per class Cross-validation details (10-fold Crossvalidation)
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0.4909 ± 0.0382 Per class Cross-validation details (10-fold Crossvalidation)
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0.3341 ± 0.0499 Cross-validation details (10-fold Crossvalidation)
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0.3988 ± 0.0452 Cross-validation details (10-fold Crossvalidation)
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0.25 ± 0.0186 Cross-validation details (10-fold Crossvalidation)
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0.3748 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.5 ± 0.0371 Cross-validation details (10-fold Crossvalidation)
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846 Per class Cross-validation details (10-fold Crossvalidation) |
0.5136 ± 0.0477 Per class Cross-validation details (10-fold Crossvalidation)
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0.5 ± 0.0371 Cross-validation details (10-fold Crossvalidation)
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1.9991 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.6669 ± 0.0495 Cross-validation details (10-fold Crossvalidation)
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0.4329 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.5 ± 0.0186 Cross-validation details (10-fold Crossvalidation)
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1.1549 ± 0.0428 Cross-validation details (10-fold Crossvalidation)
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0.5059 ± 0.0387 Cross-validation details (10-fold Crossvalidation)
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