Package fr.lip6.jkernelmachines.util.generators

Examples of fr.lip6.jkernelmachines.util.generators.GaussianGenerator

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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);
   
    svm = new DoubleSGDQN();
  }
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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 NystromLSSVM<double[]>(k);
    svm.setPercent(0.8);
    svm.setIteration(2);
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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);
   
    svm = new TSMKL<double[]>();
    svm.addKernel(new DoubleGaussL2());
  }
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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);
   
    svm = new DoubleSGD();
  }
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   */
  @Test
  public final void testValueOfIntegerInteger() {
   
    // generate data
    GaussianGenerator gen = new GaussianGenerator(2);
    List<TrainingSample<double[]>> list = gen.generateList(5, 10);
   
    DoubleLinear lin = new DoubleLinear();
    double[][] matrix = lin.getKernelMatrix(list);
   
    double[][] train = new double[5][5];
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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    GaussianGenerator g = new GaussianGenerator(2, 1, 0.5);
    list = g.generateList(nb_samples);
    dk = new DoubleGaussL2();
    nk = new NystromKernel<double[]>(dk);
  }
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    //set debug for visibility
    DebugPrinter.DEBUG_LEVEL = 2;
   
    // new generator with 10 classes and stddev of 0.5
    MultiClassGaussianGenerator mcg = new MultiClassGaussianGenerator();
    mcg.setSigma(0.5);
    mcg.setNbclasses(10);
   
    //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);
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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    mcg = new MultiClassGaussianGenerator();
  }
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  /**
   * Test method for {@link fr.lip6.jkernelmachines.util.generators.MultiClassGaussianGenerator#MultiClassGaussianGenerator(int)}.
   */
  @Test
  public final void testMultiClassGaussianGeneratorInt() {
    mcg = new MultiClassGaussianGenerator(5);
    assertEquals(5, mcg.getNbclasses());
  }
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  /**
   * @throws java.lang.Exception
   */
  @Before
  public void setUp() throws Exception {
    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);
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Related Classes of fr.lip6.jkernelmachines.util.generators.GaussianGenerator

  • 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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