| 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 | 8.722186060868105e-06 |
| 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 | 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 | 3.600096425131621e-07 |
| sklearn.svm._classes.SVC(4)_verbose | false |
0.6436 ± 0.0307 Per class Cross-validation details (10-fold Crossvalidation)
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0.4576 ± 0.0491 Per class Cross-validation details (10-fold Crossvalidation)
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0.2881 ± 0.0615 Cross-validation details (10-fold Crossvalidation)
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0.3563 ± 0.056 Cross-validation details (10-fold Crossvalidation)
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0.2671 ± 0.023 Cross-validation details (10-fold Crossvalidation)
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0.3748 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.4657 ± 0.046 Cross-validation details (10-fold Crossvalidation)
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846 Per class Cross-validation details (10-fold Crossvalidation) |
0.455 ± 0.0547 Per class Cross-validation details (10-fold Crossvalidation)
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0.4657 ± 0.046 Cross-validation details (10-fold Crossvalidation)
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1.9991 ± 0.0004 Cross-validation details (10-fold Crossvalidation)
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0.7127 ± 0.0614 Cross-validation details (10-fold Crossvalidation)
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0.4329 ± 0 Cross-validation details (10-fold Crossvalidation)
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0.5169 ± 0.0223 Cross-validation details (10-fold Crossvalidation)
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1.1939 ± 0.0515 Cross-validation details (10-fold Crossvalidation)
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0.4692 ± 0.0473 Cross-validation details (10-fold Crossvalidation)
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