Package fr.lip6.jkernelmachines.kernel.extra.bag

Examples of fr.lip6.jkernelmachines.kernel.extra.bag.UnormalizedListKernel

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      System.out.println("Error parsing file "+args[1]);
      return;
    }
   
    //setting kernel
    DoubleGaussL2 kernel = new DoubleGaussL2();
    kernel.setGamma(2.0);
   
    //setting SVM parameters
    LaSVM<double[]> svm = new LaSVM<double[]>(kernel);
    svm.setC(10); //C hyperparameter
       
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        // kernel type
        else if (args[i].equalsIgnoreCase("-k")) {
          i++;

          if (args[i].equalsIgnoreCase("gauss")) {
            kernel = new DoubleGaussL2();
          } else {
            kernel = new DoubleLinear();
          }
        }
        // algorithm
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  public void setUp() throws Exception {
   
    GaussianGenerator g = new GaussianGenerator(10, 5.0f, 1.0);
    train = g.generateList(10);
   
    DoubleGaussL2 k = new DoubleGaussL2(1.0);
    svm = new LaSVM<double[]>(k);
  }
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    MultiClassGaussianGenerator mcgg = new MultiClassGaussianGenerator(4);
    mcgg.setP(10);
    mcgg.setSigma(1);
    train = mcgg.generateList(5);
   
    DoubleGaussL2 k = new DoubleGaussL2();
    k.setGamma(0.5);
    LaSVM<double[]> svm = new LaSVM<double[]>(k);
    svm.setC(10);
    multisvm = new OneAgainstAll<double[]>(svm);
  }
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  public void setUp() throws Exception {
   
    GaussianGenerator g = new GaussianGenerator(10, 5.0f, 1.0);
    train = g.generateList(10);
   
    DoubleGaussL2 k = new DoubleGaussL2(1.0);
    svm = new LaSVM<double[]>(k);
  }
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   * Test method for
   * {@link fr.lip6.jkernelmachines.density.SMODensity#train(java.util.List)}.
   */
  @Test
  public final void testTrainListOfT() {
    DoubleGaussL2 k = new DoubleGaussL2();
    SMODensity<double[]> de = new SMODensity<double[]>(k);
    de.setC(1.);
    de.train(train);

    for (double[] x : train) {
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  public void setUp() throws Exception {
   
    GaussianGenerator g = new GaussianGenerator(10, 5.0f, 0.1);
    train = g.generateList(50);
   
    DoubleGaussL2 k = new DoubleGaussL2(1.0);
    svm = new LaSVM<double[]>(k);
    svm.setC(1.0);
  }
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   * Test method for
   * {@link fr.lip6.jkernelmachines.density.SMODensity#train(java.util.List)}.
   */
  @Test
  public final void testTrainListOfT() {
    DoubleGaussL2 k = new DoubleGaussL2();
    SimpleMKLDensity<double[]> de = new SimpleMKLDensity<double[]>();
    for(int i = 0 ; i < 2 ; i++) {
      de.addKernel(new IndexDoubleGaussL2(i));
    }
    de.addKernel(k);
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    int dim = 128;
   
    GaussianGenerator gen = new GaussianGenerator(dim, 0, 1.0);
    list = gen.generateList(dim);
   
    k = new DoubleGaussL2(2.0);
    pca = new KernelPCA<double[]>(k);
   
    pca.train(list);
  }
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  public void setUp() throws Exception {
   
    GaussianGenerator g = new GaussianGenerator(10, 5.0f, 0.1);
    train = g.generateList(50);
   
    DoubleGaussL2 k = new DoubleGaussL2(1.0);
    svm = new LaSVM<double[]>(k);
    svm.setC(1.0);
  }
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Related Classes of fr.lip6.jkernelmachines.kernel.extra.bag.UnormalizedListKernel

  • fr.lip6.jkernelmachines.classifier.DoubleLLSVM
  • fr.lip6.jkernelmachines.classifier.DoublePegasosSVM
  • fr.lip6.jkernelmachines.classifier.DoubleQNPKL
  • fr.lip6.jkernelmachines.classifier.DoubleSAG
  • fr.lip6.jkernelmachines.classifier.DoubleSGDQN
  • fr.lip6.jkernelmachines.classifier.SimpleMKL
  • fr.lip6.jkernelmachines.classifier.transductive.S3VMLightPegasos
  • fr.lip6.jkernelmachines.classifier.transductive.S3VMLightSGDQN
  • fr.lip6.jkernelmachines.density.DoubleGaussianMixtureModel
  • fr.lip6.jkernelmachines.density.SimpleMKLDensity
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