Table 4. Support vector machine regression model parameters.

Degree	Gamma	Coef0	Nu	Epsilon	Cashesize	Cost	Shrinking	Prob	P
3	0.5	0.001	0.5	0.001	100	1	1	1	0.01

Degree: set degree in kernel function; Gamma: set gamma in kernel function; Coef0: set coef0 in kernel function; Nu: set the parameter nu of nu-SVC, one-class SVM, and nu-SVR; Epsilon: set tolerance of termination criterion; Cashesize: set cache memory size in MB; Cost: set the parameter C of C-SVC, epsilon-SVR, and nu-SVR; Shrinking: whether to use the shrinking heuristics, 0 or 1; Prob: whether to train a SVR model for probability estimates, 0 or 1; P: set the epsilon in loss function of epsilon-SVR.