| 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 |
0.6778 Per class Cross-validation details (10% Holdout set)
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0.72 Per class Cross-validation details (10% Holdout set)
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0.3833 Cross-validation details (10% Holdout set)
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0.7352 Cross-validation details (10% Holdout set)
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253 Per class Cross-validation details (10% Holdout set) |
0.7303 Per class Cross-validation details (10% Holdout set)
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0.7352 Cross-validation details (10% Holdout set)
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0.9463 Cross-validation details (10% Holdout set)
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0.5771 Cross-validation details (10% Holdout set)
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0.4813 Cross-validation details (10% Holdout set)
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0.5146 Cross-validation details (10% Holdout set)
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1.0693 Cross-validation details (10% Holdout set)
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0.6778 Cross-validation details (10% Holdout set)
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