Performance improvement of function regression based on Support Vector Mmachines (SVM) by automatically tuning multiple parameters of regressors was considered.This was done by minimizing some estimation of the generalization error of SVM using gradient descent and Genetic Algorithm (GA) over the set of parameters.Performance of the proposed method was illustrated by extensive experimental results.