I use the following code to train the svm using k-fold cross-validation but the prediction accuracy is low. What I am doing wrong and how to programmatically calculate the accuracy of the classifier using cross-validation.
Log.i(TAG,"Training...");
params.set_svm_type(CvSVM.C_SVC);
params.set_kernel_type(CvSVM.RBF);
params.set_C(1.0);
params.set_degree(0.0);
params.set_coef0(0.0);
params.set_gamma(1.0);
params.set_term_crit(new TermCriteria(TermCriteria.EPS, 10000, 1e-12));
// k-fold cross validation
int kFolds = 10;
CvParamGrid C = new CvParamGrid();
CvParamGrid p = new CvParamGrid();
CvParamGrid nu = new CvParamGrid();
CvParamGrid gamma = new CvParamGrid();
CvParamGrid coeff = new CvParamGrid();
CvParamGrid degree = new CvParamGrid();
gamma.set_step(0.0);
// initialize SVM object to avoid being Null object
classifier = new CvSVM(trainingData, classes, new Mat(), new Mat(), params);
classifier.train_auto(trainingData, classes, new Mat(), new Mat(), params, kFolds, C, gamma, p, nu, coeff, degree, false);
classifier.save(XML.toString());
Log.i(TAG,"Training Done & Trained Model Saved");
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