-
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 kernel (only relevant if kernel is set to RBF)
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
sklearn.svm.libsvm.cross_validation()
2017-01-15 04:26:55
Please login to continue.