sklearn.svm.libsvm.cross_validation¶
-
sklearn.svm.libsvm.cross_validation()¶ Binding of the cross-validation routine (low-level routine)
- Parameters
- Xarray-like, dtype=float, size=[n_samples, n_features]
- Yarray, 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.
- degreeint
Degree of the polynomial kernel (only relevant if kernel is set to polynomial)
- gammafloat
Gamma parameter in rbf, poly and sigmoid kernels. Ignored by other kernels. 0.1 by default.
- coef0float
Independent parameter in poly/sigmoid kernel.
- tolfloat
Stopping criteria.
- Cfloat
C parameter in C-Support Vector Classification
- nufloat
- cache_sizefloat
- random_seedint, optional
Seed for the random number generator used for probability estimates. 0 by default.
- Returns
- targetarray, float