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(); }
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); Labels labels = new Labels(trainlab); KernelRidgeRegression krr = new KernelRidgeRegression(tau, kernel, labels); krr.train(feats_train); kernel.init(feats_train, feats_test); double[] out_labels = krr.apply().get_labels(); foreach(double item in out_labels) { Console.Write(item); } modshogun.exit_shogun(); }