| Issue | #Downvotes for this reason | By |
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| sklearn.svm._classes.SVC(17) | C-Support Vector Classification. The implementation is based on libsvm. The fit time scales at least quadratically with the number of samples and may be impractical beyond tens of thousands of samples. For large datasets consider using :class:`~sklearn.svm.LinearSVC` or :class:`~sklearn.linear_model.SGDClassifier` instead, possibly after a :class:`~sklearn.kernel_approximation.Nystroem` transformer or other :ref:`kernel_approximation`. The multiclass support is handled according to a one-vs-one scheme. For details on the precise mathematical formulation of the provided kernel functions and how `gamma`, `coef0` and `degree` affect each other, see the corresponding section in the narrative documentation: :ref:`svm_kernels`. To learn how to tune SVC's hyperparameters, see the following example: :ref:`sphx_glr_auto_examples_model_selection_plot_nested_cross_validation_iris.py` |
| sklearn.svm._classes.SVC(17)_C | 1.2 |
| sklearn.svm._classes.SVC(17)_break_ties | false |
| sklearn.svm._classes.SVC(17)_cache_size | 200 |
| sklearn.svm._classes.SVC(17)_class_weight | null |
| sklearn.svm._classes.SVC(17)_coef0 | 0.0 |
| sklearn.svm._classes.SVC(17)_decision_function_shape | "ovr" |
| sklearn.svm._classes.SVC(17)_degree | 3 |
| sklearn.svm._classes.SVC(17)_gamma | "scale" |
| sklearn.svm._classes.SVC(17)_kernel | "linear" |
| sklearn.svm._classes.SVC(17)_max_iter | -1 |
| sklearn.svm._classes.SVC(17)_probability | false |
| sklearn.svm._classes.SVC(17)_random_state | 26003 |
| sklearn.svm._classes.SVC(17)_shrinking | true |
| sklearn.svm._classes.SVC(17)_tol | 0.001 |
| sklearn.svm._classes.SVC(17)_verbose | false |
0.7283 Per class Cross-validation details (10% Holdout set)
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0.7608 Per class Cross-validation details (10% Holdout set)
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0.4753 Cross-validation details (10% Holdout set)
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0.7668 Cross-validation details (10% Holdout set)
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0.7623 Per class Cross-validation details (10% Holdout set)
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0.7668 Cross-validation details (10% Holdout set)
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0.9463 Cross-validation details (10% Holdout set)
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0.4829 Cross-validation details (10% Holdout set)
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1.0034 Cross-validation details (10% Holdout set)
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0.7283 Cross-validation details (10% Holdout set)
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