Examples of transposeTimes()


Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

      Matrix m1_czech = pca1.dissimilarityMatrix();
      for(int i = 0; i < v2_strong.getColumnDimensionality(); i++) {
        Matrix v2_i = v2_strong.getColumn(i);
        // check, if distance of v2_i to the space of rv1 > delta
        // (i.e., if v2_i spans up a new dimension)
        double dist = Math.sqrt(v2_i.transposeTimes(v2_i).get(0, 0) - v2_i.transposeTimes(m1_czech).times(v2_i).get(0, 0));

        // if so, insert v2_i into v1 and adjust v1
        // and compute m1_czech new, increase lambda1
        if(lambda1 < dimensionality && dist > delta) {
          adjust(v1, e1_czech, v2_i, lambda1++);
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

      Matrix m1_czech = pca1.dissimilarityMatrix();
      for(int i = 0; i < v2_strong.getColumnDimensionality(); i++) {
        Matrix v2_i = v2_strong.getColumn(i);
        // check, if distance of v2_i to the space of rv1 > delta
        // (i.e., if v2_i spans up a new dimension)
        double dist = Math.sqrt(v2_i.transposeTimes(v2_i).get(0, 0) - v2_i.transposeTimes(m1_czech).times(v2_i).get(0, 0));

        // if so, insert v2_i into v1 and adjust v1
        // and compute m1_czech new, increase lambda1
        if(lambda1 < dimensionality && dist > delta) {
          adjust(v1, e1_czech, v2_i, lambda1++);
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

      Matrix m2_czech = pca2.dissimilarityMatrix();
      for(int i = 0; i < v1_strong.getColumnDimensionality(); i++) {
        Matrix v1_i = v1_strong.getColumn(i);
        // check, if distance of v1_i to the space of rv2 > delta
        // (i.e., if v1_i spans up a new dimension)
        double dist = Math.sqrt(v1_i.transposeTimes(v1_i).get(0, 0) - v1_i.transposeTimes(m2_czech).times(v1_i).get(0, 0));

        // if so, insert v1_i into v2 and adjust v2
        // and compute m2_czech new , increase lambda2
        if(lambda2 < dimensionality && dist > delta) {
          adjust(v2, e2_czech, v1_i, lambda2++);
View Full Code Here

Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

      Matrix m2_czech = pca2.dissimilarityMatrix();
      for(int i = 0; i < v1_strong.getColumnDimensionality(); i++) {
        Matrix v1_i = v1_strong.getColumn(i);
        // check, if distance of v1_i to the space of rv2 > delta
        // (i.e., if v1_i spans up a new dimension)
        double dist = Math.sqrt(v1_i.transposeTimes(v1_i).get(0, 0) - v1_i.transposeTimes(m2_czech).times(v1_i).get(0, 0));

        // if so, insert v1_i into v2 and adjust v2
        // and compute m2_czech new , increase lambda2
        if(lambda2 < dimensionality && dist > delta) {
          adjust(v2, e2_czech, v1_i, lambda2++);
View Full Code Here

Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

    Matrix v2_strong = pca2.adapatedStrongEigenvectors();
    for(int i = 0; i < v2_strong.getColumnDimensionality(); i++) {
      Matrix v2_i = v2_strong.getColumn(i);
      // check, if distance of v2_i to the space of pca_1 > delta
      // (i.e., if v2_i spans up a new dimension)
      double dist = Math.sqrt(v2_i.transposeTimes(v2_i).get(0, 0) - v2_i.transposeTimes(m1_czech).times(v2_i).get(0, 0));

      // if so, return false
      if(dist > delta) {
        return false;
      }
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Matrix.transposeTimes()

    Matrix v2_strong = pca2.adapatedStrongEigenvectors();
    for(int i = 0; i < v2_strong.getColumnDimensionality(); i++) {
      Matrix v2_i = v2_strong.getColumn(i);
      // check, if distance of v2_i to the space of pca_1 > delta
      // (i.e., if v2_i spans up a new dimension)
      double dist = Math.sqrt(v2_i.transposeTimes(v2_i).get(0, 0) - v2_i.transposeTimes(m1_czech).times(v2_i).get(0, 0));

      // if so, return false
      if(dist > delta) {
        return false;
      }
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.transposeTimes()

    // for each object compute Mahalanobis distance
    for(DBID id : relation.iterDBIDs()) {
      V x = relation.get(id);
      Vector x_minus_mean = x.minus(mean).getColumnVector();
      // Gaussian PDF
      final double mDist = x_minus_mean.transposeTimes(covarianceTransposed).times(x_minus_mean).get(0, 0);
      final double prob = fakt * Math.exp(-mDist / 2.0);

      mm.put(prob);
      oscores.put(id, prob);
    }
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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.transposeTimes()

    // for each object compute probability and sum
    for(DBID id : objids) {
      V x = database.get(id);

      Vector x_minus_mean = x.minus(mean).getColumnVector();
      double mDist = x_minus_mean.transposeTimes(covInv).times(x_minus_mean).get(0, 0);
      prob += Math.log(fakt * Math.exp(-mDist / 2.0));
    }
    return prob;
  }

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Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.transposeTimes()

      Matrix m1_czech = pca1.dissimilarityMatrix();
      for(int i = 0; i < v2_strong.getColumnDimensionality(); i++) {
        Vector v2_i = v2_strong.getCol(i);
        // check, if distance of v2_i to the space of rv1 > delta
        // (i.e., if v2_i spans up a new dimension)
        double dist = Math.sqrt(v2_i.transposeTimes(v2_i) - v2_i.transposeTimesTimes(m1_czech, v2_i));

        // if so, insert v2_i into v1 and adjust v1
        // and compute m1_czech new, increase lambda1
        if(lambda1 < dimensionality && dist > delta) {
          adjust(v1, e1_czech, v2_i, lambda1++);
View Full Code Here

Examples of de.lmu.ifi.dbs.elki.math.linearalgebra.Vector.transposeTimes()

      Matrix m2_czech = pca2.dissimilarityMatrix();
      for(int i = 0; i < v1_strong.getColumnDimensionality(); i++) {
        Vector v1_i = v1_strong.getCol(i);
        // check, if distance of v1_i to the space of rv2 > delta
        // (i.e., if v1_i spans up a new dimension)
        double dist = Math.sqrt(v1_i.transposeTimes(v1_i) - v1_i.transposeTimes(m2_czech).times(v1_i).get(0));

        // if so, insert v1_i into v2 and adjust v2
        // and compute m2_czech new , increase lambda2
        if(lambda2 < dimensionality && dist > delta) {
          adjust(v2, e2_czech, v1_i, lambda2++);
View Full Code Here
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