sklearn.svm.libsvm.predict
-
sklearn.svm.libsvm.predict() -
Predict target values of X given a model (low-level method)
| Parameters: |
-
X : array-like, dtype=float, size=[n_samples, n_features] -
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’} -
Type of kernel. -
degree : int -
Degree of the polynomial kernel. -
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. |
| Returns: |
-
dec_values : array -
predicted values. |