public static void main(String argv[]) {
    modshogun.init_shogun_with_defaults();
    double width = 1.4;
    int size_cache = 10;

    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);

    NormOne preproc = new NormOne();
    preproc.init(feats_train);
    feats_train.add_preprocessor(preproc);
    feats_train.apply_preprocessor();
    feats_test.add_preprocessor(preproc);
    feats_test.apply_preprocessor();

    Chi2Kernel kernel = new Chi2Kernel(feats_train, feats_train, width, size_cache);

    DoubleMatrix km_train = kernel.get_kernel_matrix();
    kernel.init(feats_train, feats_test);
    DoubleMatrix km_test = kernel.get_kernel_matrix();

    System.out.println(km_train.toString());
    System.out.println(km_test.toString());
  }
  public static void main(String argv[]) {
    modshogun.init_shogun_with_defaults();
    double width = 2.1;
    double epsilon = 1e-5;
    double C = 1.0;
    int mkl_norm = 2;

    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");

    CombinedKernel kernel = new CombinedKernel();
    CombinedFeatures feats_train = new CombinedFeatures();
    CombinedFeatures feats_test = new CombinedFeatures();

    RealFeatures subkfeats1_train = new RealFeatures(traindata_real);
    RealFeatures subkfeats1_test = new RealFeatures(testdata_real);

    GaussianKernel subkernel = new GaussianKernel(10, width);
    feats_train.append_feature_obj(subkfeats1_train);
    feats_test.append_feature_obj(subkfeats1_test);
    kernel.append_kernel(subkernel);

    RealFeatures subkfeats2_train = new RealFeatures(traindata_real);
    RealFeatures subkfeats2_test = new RealFeatures(testdata_real);

    LinearKernel subkernel2 = new LinearKernel();
    feats_train.append_feature_obj(subkfeats2_train);
    feats_test.append_feature_obj(subkfeats2_test);
    kernel.append_kernel(subkernel2);

    RealFeatures subkfeats3_train = new RealFeatures(traindata_real);
    RealFeatures subkfeats3_test = new RealFeatures(testdata_real);

    PolyKernel subkernel3 = new PolyKernel(10, 2);
    feats_train.append_feature_obj(subkfeats3_train);
    feats_test.append_feature_obj(subkfeats3_test);
    kernel.append_kernel(subkernel3);

    kernel.init(feats_train, feats_train);

    Labels labels = new Labels(trainlab);

    MKLMultiClass mkl = new MKLMultiClass(C, kernel, labels);
    mkl.set_epsilon(epsilon);
    mkl.set_mkl_epsilon(epsilon);
    mkl.set_mkl_norm(mkl_norm);

    mkl.train();

    kernel.init(feats_train, feats_test);
    DoubleMatrix out = mkl.apply().get_labels();

    modshogun.exit_shogun();
  }
  public static void main(String argv[]) {
    modshogun.init_shogun_with_defaults();

    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);

    EuclideanDistance distance = new EuclideanDistance(feats_train, feats_train);

    DoubleMatrix dm_train = distance.get_distance_matrix();
    distance.init(feats_train, feats_test);
    DoubleMatrix dm_test = distance.get_distance_matrix();

    System.out.println(dm_train.toString());
    System.out.println(dm_test.toString());
  }
Ejemplo n.º 4
0
  static ArrayList run(int para) {
    modshogun.init_shogun_with_defaults();
    int k = para;
    init_random(17);

    DoubleMatrix fm_train = Load.load_numbers("../data/fm_train_real.dat");

    RealFeatures feats_train = new RealFeatures(fm_train);
    EuclidianDistance distance = new EuclidianDistance(feats_train, feats_train);

    KMeans kmeans = new KMeans(k, distance);
    kmeans.train();

    DoubleMatrix out_centers = kmeans.get_cluster_centers();
    kmeans.get_radiuses();

    ArrayList result = new ArrayList();
    result.add(kmeans);
    result.add(out_centers);

    modshogun.exit_shogun();
    return result;
  }