public static void Main()
{
modshogun.init_shogun_with_defaults();
double width = 0.8;
int C = 1;
double epsilon = 1e-5;
double tube_epsilon = 1e-2;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
RegressionLabels labels = new RegressionLabels(trainlab);
LibSVR svr = new LibSVR(C, epsilon, kernel, labels);
svr.set_tube_epsilon(tube_epsilon);
svr.train();
kernel.init(feats_train, feats_test);
double[] out_labels = RegressionLabels.obtain_from_generic(svr.apply()).get_labels();
foreach (double item in out_labels)
{
Console.Write(out_labels);
}
modshogun.exit_shogun();
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double width = 0.8;
double tau = 1e-6;
double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat");
double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat");
double[] trainlab = Load.load_labels("../data/label_train_twoclass.dat");
RealFeatures feats_train = new RealFeatures(traindata_real);
RealFeatures feats_test = new RealFeatures(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
RegressionLabels labels = new RegressionLabels(trainlab);
KernelRidgeRegression krr = new KernelRidgeRegression(tau, kernel, labels);
krr.train(feats_train);
kernel.init(feats_train, feats_test);
double[] out_labels = RegressionLabels.obtain_from_generic(krr.apply()).get_labels();
foreach (double item in out_labels)
{
Console.Write(item);
}
modshogun.exit_shogun();
}