static void Main(string[] argv)
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat");
DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat");
DoubleMatrix trainlab = Load.load_labels("../data/label_train_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
Labels labels = new Labels(trainlab);
GMNPSVM svm = new GMNPSVM(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();
kernel.init(feats_train, feats_test);
DoubleMatrix out_labels = svm.apply(feats_test).get_labels();
Console.WriteLine(out_labels.ToString());
modshogun.exit_shogun();
}
public static void Main() {
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
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_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
MulticlassLabels labels = new MulticlassLabels(trainlab);
GMNPSVM svm = new GMNPSVM(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();
kernel.init(feats_train, feats_test);
double[] out_labels = LabelsFactory.to_multiclass(svm.apply(feats_test)).get_labels();
foreach(double item in out_labels) {
Console.Write(item);
}
}
public static void Main()
{
modshogun.init_shogun_with_defaults();
double width = 2.1;
double epsilon = 1e-5;
double C = 1.0;
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_multiclass.dat");
RealFeatures feats_train = new RealFeatures();
feats_train.set_feature_matrix(traindata_real);
RealFeatures feats_test = new RealFeatures();
feats_test.set_feature_matrix(testdata_real);
GaussianKernel kernel = new GaussianKernel(feats_train, feats_train, width);
MulticlassLabels labels = new MulticlassLabels(trainlab);
GMNPSVM svm = new GMNPSVM(C, kernel, labels);
svm.set_epsilon(epsilon);
svm.train();
kernel.init(feats_train, feats_test);
double[] out_labels = LabelsFactory.to_multiclass(svm.apply(feats_test)).get_labels();
foreach (double item in out_labels)
{
Console.Write(item);
}
}
