// run from build folder of the project (see path below)
int main (int argc, char** argv) {
Eigen::MatrixXf X;
Eigen::MatrixXf y;
eigen_extensions::loadASCII("../test/svmtestx.eig.txt", &X);
eigen_extensions::loadASCII("../test/svmtesty.eig.txt", &y);
// Classify
cout << X.topRows(5) << endl;
cout << y.topRows(5) << endl;
vector<int> yhat;
SVMClassifier svm;
svm.train(X, y);
svm.test(X, yhat);
Eigen::MatrixXf w;
float b;
svm.getw(w, b);
Eigen::MatrixXf margin= ((X * w).array() + b).matrix(); // ahh eigen...
// Evaluate accuracy and print results
int match=0;
for(int i=0;i<yhat.size();i++) {
if(yhat[i]==(int)y(i)) match++; else printf("WRONG! ");
printf("y= %d, yhat= %d margin= %f\n", (int)y(i), yhat[i], margin(i));
}
printf("MATLAB cross-check: last margin should be around -3.107\n");
printf("Accuracy= %f. From MATLAB cross-check, expect this to be around 0.945\n", 1.0*match/yhat.size());
// Save the model
svm.saveModel("temp.svmmodel");
// Test loading model in new instance of SVMClassifier
SVMClassifier svm2;
svm2.loadModel("temp.svmmodel");
yhat.clear();
svm2.test(X, yhat);
match=0;
for(int i=0;i<yhat.size();i++) if(yhat[i]==(int)y(i)) match++;
printf("Accuracy= %f from loaded model. Should be 0.945 again.\n", 1.0*match/yhat.size());
printf("you may want to rm the temporary file temp.svmmodel\n");
}
