Package weka.core.matrix

Examples of weka.core.matrix.Matrix

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   * @param variance the variance
   * @return the value for a normal kernel
   */
  private double normalKernel(double x) {
   
    Matrix thisPoint = new Matrix(1, 2);
    thisPoint.set(0, 0, x);
    thisPoint.set(0, 1, m_ConstDelta);
    return Math.exp(-thisPoint.times(m_CovarianceInverse).
        times(thisPoint.transpose()).get(0, 0)
        / 2) / (Math.sqrt(TWO_PI) * m_Determinant);
  }
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      if (denom == 0) {
        return;
      }
      m_Determinant = covariance.get(0, 0) * covariance.get(1, 1)
      - covariance.get(1, 0) * covariance.get(0, 1);
      m_CovarianceInverse = new Matrix(2, 2);
      m_CovarianceInverse.set(0, 0, 1.0 / a + b * c / a / a / denom);
      m_CovarianceInverse.set(0, 1, -b / a / denom);
      m_CovarianceInverse.set(1, 0, -c / a / denom);
      m_CovarianceInverse.set(1, 1, 1.0 / denom);
      m_ConstDelta = constDelta;
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    try {
      double delta = 0.5;
      double xmean = 0;
      double lower = 0;
      double upper = 10;
      Matrix covariance = new Matrix(2, 2);
      covariance.set(0, 0, 2);
      covariance.set(0, 1, -3);
      covariance.set(1, 0, -4);
      covariance.set(1, 1, 5);
      if (argv.length > 0) {
        covariance.set(0, 0, Double.valueOf(argv[0]).doubleValue());
      }
      if (argv.length > 1) {
        covariance.set(0, 1, Double.valueOf(argv[1]).doubleValue());
      }
      if (argv.length > 2) {
        covariance.set(1, 0, Double.valueOf(argv[2]).doubleValue());
      }
      if (argv.length > 3) {
        covariance.set(1, 1, Double.valueOf(argv[3]).doubleValue());
      }
      if (argv.length > 4) {
        delta = Double.valueOf(argv[4]).doubleValue();
      }
      if (argv.length > 5) {
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Related Classes of weka.core.matrix.Matrix

  • weka.attributeSelection.LatentSemanticAnalysis
  • weka.classifiers.functions.GaussianProcesses
  • weka.classifiers.functions.pace.PaceMatrix
  • weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
  • weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernelTest
  • weka.classifiers.trees.BFTree
  • weka.classifiers.trees.SimpleCart
  • weka.clusterers.sIB
  • weka.clusterers.sIB$Partition
  • weka.estimators.MahalanobisEstimator
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