18730 0 7 2021-01-03T13:18:30Z openml==0.11.0,sklearn==0.24.0 sklearn==0.24.0 numpy>=1.6.1 scipy>=0.9 sklearn.svm._classes.SVC 0 sklearn.svm._classes.SVC public 0 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. 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`.