sklearn.svm.libsvm.cross_validation

sklearn.svm.libsvm.cross_validation()

Binding of the cross-validation routine (low-level routine)

Parameters:

X : array-like, dtype=float, size=[n_samples, n_features] Y : array, dtype=float, size=[n_samples] target vector svm_type : {0, 1, 2, 3, 4} Type of SVM: C SVC, nu SVC, one class, epsilon SVR, nu SVR kernel : {‘linear’, ‘rbf’, ‘poly’, ‘sigmoid’, ‘precomputed’} Kernel to use in the model: linear, polynomial, RBF, sigmoid or precomputed. degree : int Degree of the polynomial kernel (only relevant if kernel is set to polynomial) gamma : float Gamma parameter in rbf, poly and sigmoid kernels. Ignored by other kernels. 0.1 by default. coef0 : float Independent parameter in poly/sigmoid kernel. tol : float Stopping criteria. C : float C parameter in C-Support Vector Classification nu : float cache_size : float random_seed : int, optional Seed for the random number generator used for probability estimates. 0 by default.

Returns:

target : array, float