public virtual object run(IList para) { modshogun.init_shogun_with_defaults(); int cardinality = (int)((int?)para[0]); int size_cache = (int)((int?)para[1]); DoubleMatrix traindata_real = Load.load_numbers("../data/fm_train_real.dat"); DoubleMatrix testdata_real = Load.load_numbers("../data/fm_test_real.dat"); RealFeatures feats_train = new RealFeatures(traindata_real); RealFeatures feats_test = new RealFeatures(testdata_real); ANOVAKernel kernel = new ANOVAKernel(feats_train, feats_train, cardinality, size_cache); DoubleMatrix km_train = kernel.get_kernel_matrix(); kernel.init(feats_train, feats_test); DoubleMatrix km_test = kernel.get_kernel_matrix(); ArrayList result = new ArrayList(); result.Add(km_train); result.Add(km_test); result.Add(kernel); modshogun.exit_shogun(); return (object)result; }
public static void Main() { modshogun.init_shogun_with_defaults(); int cardinality = 2; int size_cache = 5; double[,] traindata_real = Load.load_numbers("../data/fm_train_real.dat"); double[,] testdata_real = Load.load_numbers("../data/fm_test_real.dat"); RealFeatures feats_train = new RealFeatures(traindata_real); RealFeatures feats_test = new RealFeatures(testdata_real); ANOVAKernel kernel = new ANOVAKernel(feats_train, feats_train, cardinality, size_cache); double[,] km_train = kernel.get_kernel_matrix(); kernel.init(feats_train, feats_test); double[,] km_test = kernel.get_kernel_matrix(); }
internal static HandleRef getCPtr(ANOVAKernel obj) { return((obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr); }
internal static HandleRef getCPtr(ANOVAKernel obj) { return (obj == null) ? new HandleRef(null, IntPtr.Zero) : obj.swigCPtr; }