static void Main(string[] argv) { modshogun.init_shogun_with_defaults(); int k = 3; 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(traindata_real); RealFeatures feats_test = new RealFeatures(testdata_real); EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train); Labels labels = new Labels(trainlab); KNN knn = new KNN(k, distance, labels); knn.train(); DoubleMatrix out_labels = knn.apply(feats_test).get_labels(); Console.WriteLine(out_labels.ToString()); modshogun.exit_shogun(); }
public static void Main() { modshogun.init_shogun_with_defaults(); int k = 3; 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(traindata_real); RealFeatures feats_test = new RealFeatures(testdata_real); EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train); Labels labels = new Labels(trainlab); KNN knn = new KNN(k, distance, labels); knn.train(); double[] out_labels = knn.apply(feats_test).get_labels(); foreach(double item in out_labels) { Console.Write(item); } modshogun.exit_shogun(); }
public static void Main() { modshogun.init_shogun_with_defaults(); int k = 3; 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(traindata_real); RealFeatures feats_test = new RealFeatures(testdata_real); EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train); MulticlassLabels labels = new MulticlassLabels(trainlab); KNN knn = new KNN(k, distance, labels); knn.train(); double[] out_labels = MulticlassLabels.obtain_from_generic(knn.apply(feats_test)).get_labels(); foreach (double item in out_labels) { Console.Write(item); } modshogun.exit_shogun(); }