SVM训练时交叉验证参数最优选择

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void SVMExample::InitParams()
{
param.svm_type = C_SVC;
param.kernel_type = RBF;
param.degree = 3;
param.gamma = (double)1/30;
param.coef0 = 0;
param.nu = 0.5;
param.cache_size = 100;
param.C = 4;
param.eps = 1e-3;
param.p = 0.1;
param.shrinking = 1;
param.probability = 1;
param.nr_weight = 0;
param.weight_label = NULL;
param.weight = NULL;
DoCrossValidation();

}

void SVMExample::DoCrossValidation()
{
int gBegin, gEnd, gStep, cBegin, cEnd, cStep;
int nrFold = 5;
gBegin = -15; gEnd = 3; gStep = 1;
cBegin = -5; cEnd = 15; cStep = 1;
double tempG, tempC, bestG, bestC;
double bestAccuracy = 0;

for (int i=gBegin; i<=gEnd; i+=gStep)
{
tempG = pow(2.0, 1.0*i);
param.gamma = tempG;
for (int j=cBegin; j<=cEnd; j+=cStep)
{
double *target = new double[prob.l];
int totalCorrect = 0;
tempC = pow(2.0, 1.0*j);
param.C = tempC;

svm_cross_validation(&prob, &param, nrFold, target);
for (int k=0; k<prob.l; k++)
{
if (target[k] == prob.y[k])
{
totalCorrect++;
}
}
if ((totalCorrect*1.0/prob.l) > bestAccuracy)
{
bestC = tempC;
bestG = tempG;
bestAccuracy = totalCorrect*1.0/prob.l;
}
delete []target;
}
}
param.C = bestC;
param.gamma = bestG;
printf("bestC : %lf ", bestC);
printf("bestG : %lf ", bestG);
printf("bestAccuracy : %lf\n", bestAccuracy);
}