Package fr.lip6.jkernelmachines.threading

Examples of fr.lip6.jkernelmachines.threading.ThreadedMatrixOperator

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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    GaussianGenerator gen = new GaussianGenerator(2, 2, 1.0);
    List<TrainingSample<double[]>> list = gen.generateList(100, 100);
    train = new ArrayList<double[]>();
    for (TrainingSample<double[]> t : list) {
      train.add(t.sample);
    }
  }
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  /**
   * Test method for {@link fr.lip6.jkernelmachines.util.generators.GaussianGenerator#GaussianGenerator(int, float, double)}.
   */
  @Test
  public final void testGaussianGeneratorIntFloatDouble() {
    g = new GaussianGenerator(2, 4.0f, 1.0);
    assertEquals(2, g.getDimension());
    assertEquals(4.0f, g.getP(), 1e-15);
    assertEquals(1.0, g.getSigma(), 1e-15);
  }
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  LaSVM<double[]> svm;

  @Before
  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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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    GaussianGenerator gen = new GaussianGenerator(2, 2, 1.0);
    List<TrainingSample<double[]>> list = gen.generateList(100, 100);
    train = new ArrayList<double[]>();
    for (TrainingSample<double[]> t : list) {
      train.add(t.sample);
    }
  }
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  @Before
  public void setUp() throws Exception {
   
    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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  LaSVM<double[]> svm;

  @Before
  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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   */
  @Before
  public void setUp() throws Exception {
   

    GaussianGenerator gen = new GaussianGenerator(dim);
    list = gen.generateList(nbSamples);
   
   
    pca = new DoublePCA();
    pca.train(list);
   
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  LaSVM<double[]> svm;

  @Before
  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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   * @throws java.lang.Exception
   */
  @Before
  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 LaSVMI<double[]>(k);
  }
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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    GaussianGenerator gen = new GaussianGenerator(2, 2, 1.0);
    List<TrainingSample<double[]>> list = gen.generateList(100, 100);
    train = new ArrayList<double[]>();
    for (TrainingSample<double[]> t : list) {
      train.add(t.sample);
    }
  }
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  • 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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