Package fr.lip6.jkernelmachines.classifier.transductive

Examples of fr.lip6.jkernelmachines.classifier.transductive.S3VMLightPegasos.train()

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      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");

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      }
      for (int d = 1; d < 5; d++) {
        svm.addKernel(new DoublePolynomial(d));
        svm.addKernel(new DoubleHPolynomial(d));
      }
      svm.train(localTrain);

      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
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        .toString())) {
      DoubleQNPKL svm = new DoubleQNPKL();
      svm.setC(Double.parseDouble(regularizationField.getText()));
      DebugPrinter.setDebugLevel(2);

      svm.train(localTrain);
      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
      for (int s = 0; s < alphas.length; s++) {
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      peg.setLambda(lambda);
      peg.setK(K);
      peg.setT(T);
      peg.setT0(t0);
      peg.setBias(bias);
      peg.train(train);


      //3.2 train transductive pegasos
//      DoubleGaussL2 kernel = new DoubleGaussL2();
//      kernel.setGamma(0.01);
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        .toString())) {
      DoubleQNPKL svm = new DoubleQNPKL();
      svm.setC(Double.parseDouble(regularizationField.getText()));
      DebugPrinter.setDebugLevel(2);

      svm.train(localTrain);
      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
      for (int s = 0; s < alphas.length; s++) {
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        .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");

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      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");

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      }
      for (int d = 1; d < 5; d++) {
        svm.addKernel(new DoublePolynomial(d));
        svm.addKernel(new DoubleHPolynomial(d));
      }
      svm.train(localTrain);

      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
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        .toString())) {
      DoubleQNPKL svm = new DoubleQNPKL();
      svm.setC(Double.parseDouble(regularizationField.getText()));
      DebugPrinter.setDebugLevel(2);

      svm.train(localTrain);
      // info
      classnameLabel.setText(svm.getClass().getSimpleName());
      double[] alphas = svm.getAlphas();
      int sv = 0;
      for (int s = 0; s < alphas.length; s++) {
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      tpeg.setT(T);
      tpeg.setT0(t0);
      tpeg.setBias(bias);
//      tpeg.setVerbosityLevel(3);
      tpeg.setNumplus(200);
      tpeg.train(train, test);
     

      //6. test svm
      int nbErr = 0;
      int tpegErr = 0;
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