Examples of DoubleGaussL2

fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2
Gaussian Kernel on double[] that uses a L2 distance. @author dpicard

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

    if ("lasvm"
        .equalsIgnoreCase(classifierBox.getSelectedItem().toString())) {
      Kernel<double[]> k = new DoubleLinear();
      if ("GaussianL2".equalsIgnoreCase(kernelBox.getSelectedItem()
          .toString())) {
        k = new DoubleGaussL2(Double.parseDouble(kernelParamTextField
            .getText()));
      } else if ("TriangleL2".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoubleTriangleL2(
            Double.parseDouble(kernelParamTextField.getText()));
      } else if ("Polynomial".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoublePolynomial(Integer.parseInt(kernelParamTextField
            .getText()));
      } else if ("HPlolynomial".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoubleHPolynomial(Integer.parseInt(kernelParamTextField
            .getText()));
      }


      LaSVM<double[]> svm = new LaSVM<double[]>(k);
      svm.setC(Double.parseDouble(regularizationField.getText()));
      svm.train(localTrain);


      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
      for (int s = 0; s < alphas.length; s++) {
        if (alphas[s] != 0) {
          sv++;
        }
      }
      svLabel.setText("" + sv);
      validate();
      // save current classifier
      model.classifier = svm;
    } else if ("smo".equalsIgnoreCase(classifierBox.getSelectedItem()
        .toString())) {
      Kernel<double[]> k = new DoubleLinear();
      if ("GaussianL2".equalsIgnoreCase(kernelBox.getSelectedItem()
          .toString())) {
        k = new DoubleGaussL2(Double.parseDouble(kernelParamTextField
            .getText()));
      } else if ("TriangleL2".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoubleTriangleL2(
            Double.parseDouble(kernelParamTextField.getText()));
      } else if ("Polynomial".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoublePolynomial(Integer.parseInt(kernelParamTextField
            .getText()));
      } else if ("HPlolynomial".equalsIgnoreCase(kernelBox
          .getSelectedItem().toString())) {
        k = new DoubleHPolynomial(Integer.parseInt(kernelParamTextField
            .getText()));
      }


      SMOSVM<double[]> svm = new SMOSVM<double[]>(k);
      svm.setC(Double.parseDouble(regularizationField.getText()));
      svm.train(localTrain);


      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
      for (int s = 0; s < alphas.length; s++) {
        if (alphas[s] != 0) {
          sv++;
        }
      }
      svLabel.setText("" + sv);
      validate();
      // save current classifier
      model.classifier = svm;
    } else if ("sag".equalsIgnoreCase(classifierBox.getSelectedItem()
        .toString())) {
      DoubleSAG svm = new DoubleSAG();
      svm.setLambda(1. / (train.size() * Double
          .parseDouble(regularizationField.getText())));
      svm.setE(10);
      svm.train(localTrain);


      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      svLabel.setText("N/A");


      // save current classifier
      model.classifier = svm;
    } else if ("pegasos".equalsIgnoreCase(classifierBox.getSelectedItem()
        .toString())) {
      DoublePegasosSVM svm = new DoublePegasosSVM();


      svm.setLambda(1. / (train.size() * Double
          .parseDouble(regularizationField.getText())));
      svm.setK(train.size() / 20);
      svm.setT(10 * train.size());
      svm.train(localTrain);


      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      svLabel.setText("N/A");


      // save current classifier
      model.classifier = svm;
    } else if ("simplemkl".equalsIgnoreCase(classifierBox.getSelectedItem()
        .toString())) {
      SimpleMKL<double[]> svm = new SimpleMKL<double[]>();
      svm.setC(Double.parseDouble(regularizationField.getText()));


      double[] G = { 0.05, 0.1, 0.2, 0.4, 0.8, 1.6, 3.2, 6.4, 12.8, 25.6 };
//      int dim = train.get(0).sample.length;
      for (double g : G) {
        svm.addKernel(new DoubleGaussL2(g));
//        // for(int i = 0 ; i < dim ; i++) {
//        // IndexDoubleGaussL2 k = new IndexDoubleGaussL2(i);
//        // k.setGamma(g);
//        // svm.addKernel(k);
//        // }

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

    
    //generate the list
    List<TrainingSample<double[]>> list = mcg.generateList(100);
    
    //build classifier based on GaussL2 lasvm with c=10
    DoubleGaussL2 k =new DoubleGaussL2(2);
    LaSVM<double[]> svm = new LaSVM<double[]>(k);
    svm.setC(10);
    OneAgainstAll<double[]> mcsvm = new OneAgainstAll<double[]>(svm);

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

      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

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

        // kernel type
        else if (args[i].equalsIgnoreCase("-k")) {
          i++;


          if (args[i].equalsIgnoreCase("gauss")) {
            kernel = new DoubleGaussL2();
          } else {
            kernel = new DoubleLinear();
          }
        }
        // algorithm

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

  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);
  }

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

    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);
  }

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

  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);
  }

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

   * 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) {

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

  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);
  }

View Full Code Here

Examples of fr.lip6.jkernelmachines.kernel.typed.DoubleGaussL2

   * 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);

View Full Code Here

0 1 2 3

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.