List of aggregateColumns() Examples

Examples of aggregateColumns()

org.apache.mahout.math.DenseMatrix.aggregateColumns()
org.apache.mahout.math.Matrix.aggregateColumns()
Collects the results of a function applied to each column of a matrix. @param f The function to be applied to each column. @return The vector of results.

Examples of org.apache.mahout.math.DenseMatrix.aggregateColumns()

      x.viewRow(row).assign(c.viewPart(0, 5));
      row++;
    }


    // Verify that each column looks right. Should contain zeros except for a single 6.
    final Vector columnNorms = x.aggregateColumns(new VectorFunction() {
      @Override
      public double apply(Vector f) {
        // Return the sum of three discrepancy measures.
        return Math.abs(f.minValue()) + Math.abs(f.maxValue() - 6) + Math.abs(f.norm(1) - 6);
      }

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Examples of org.apache.mahout.math.DenseMatrix.aggregateColumns()

      x.viewRow(row).assign(c.viewPart(0, 5));
      row++;
    }


    // Verify that each column looks right. Should contain zeros except for a single 6.
    final Vector columnNorms = x.aggregateColumns(new VectorFunction() {
      @Override
      public double apply(Vector f) {
        // Return the sum of three discrepancy measures.
        return Math.abs(f.minValue()) + Math.abs(f.maxValue() - 6) + Math.abs(f.norm(1) - 6);
      }

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Examples of org.apache.mahout.math.Matrix.aggregateColumns()

      x.viewRow(row).assign(c.viewPart(0, 5));
      row++;
    }


    // Verify that each column looks right. Should contain zeros except for a single 6.
    final Vector columnNorms = x.aggregateColumns(new VectorFunction() {
      @Override
      public double apply(Vector f) {
        // Return the sum of three discrepancy measures.
        return Math.abs(f.minValue()) + Math.abs(f.maxValue() - 6) + Math.abs(f.norm(1) - 6);
      }

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Examples of org.apache.mahout.math.Matrix.aggregateColumns()

      x.viewRow(row).assign(c.viewPart(0, 5));
      row++;
    }


    // Verify that each column looks right. Should contain zeros except for a single 6.
    final Vector columnNorms = x.aggregateColumns(new VectorFunction() {
      @Override
      public double apply(Vector f) {
        // Return the sum of three discrepancy measures.
        return Math.abs(f.minValue()) + Math.abs(f.maxValue() - 6) + Math.abs(f.norm(1) - 6);
      }

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