List of viewColumn() Examples

Examples of viewColumn()

cern.colt.matrix.DoubleMatrix2D.viewColumn()
Constructs and returns a new slice view representing the rows of the given column. The returned view is backed by this matrix, so changes in the returned view are reflected in this matrix, and vice-versa. To obtain a slice view on subranges, construct a sub-ranging view (viewPart(...)), then apply this method to the sub-range view.
Example:

2 x 3 matrix:
1, 2, 3
4, 5, 6 viewColumn(0) ==> Matrix1D of size 2:
1, 4

@param column the column to fix. @return a new slice view. @throws IndexOutOfBoundsException if column < 0 || column>= columns(). @see #viewRow(int)
cern.colt.matrix.impl.DenseDoubleMatrix2D.viewColumn()
org.apache.mahout.math.DenseMatrix.viewColumn()
org.apache.mahout.math.Matrix.viewColumn()
org.apache.mahout.math.matrix.DoubleMatrix2D.viewColumn()
Constructs and returns a new slice view representing the rows of the given column. The returned view is backed by this matrix, so changes in the returned view are reflected in this matrix, and vice-versa. To obtain a slice view on subranges, construct a sub-ranging view (viewPart(...)), then apply this method to the sub-range view.
Example:

2 x 3 matrix:
1, 2, 3
4, 5, 6 viewColumn(0) ==> Matrix1D of size 2:
1, 4

@param column the column to fix. @return a new slice view. @throws IndexOutOfBoundsException if column < 0 || column>= columns(). @see #viewRow(int)

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

    values[1][1] = 0.0;
    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    values[1][1] = 0.0;
    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    Matrix u = generateDenseOrthonormalRandom(m, svCnt, rnd);


    // apply singular values
    Matrix mx = m > n ? v : u;
    for (int i = 0; i < svCnt; i++) {
      mx.assignColumn(i, mx.viewColumn(i).times(svalues.getQuick(i)));
    }


    SequenceFile.Writer w =
      SequenceFile.createWriter(dfs,
                                dfs.getConf(),

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

    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    trainer.train(labelset, dataset);
    assertTrue(trainer.getModel().classify(dataset.viewColumn(3)));
    assertFalse(trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    Matrix u = generateDenseOrthonormalRandom(m, svCnt, rnd);


    // apply singular values
    Matrix mx = m > n ? v : u;
    for (int i = 0; i < svCnt; i++) {
      mx.assignColumn(i, mx.viewColumn(i).times(svalues.getQuick(i)));
    }


    SequenceFile.Writer w =
      SequenceFile.createWriter(dfs,
                                dfs.getConf(),

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

    values[1][1] = 0.0;
    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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

    values[2][2] = 0.0;


    Matrix dataset = new DenseMatrix(values);
    this.trainer.train(labelset, dataset);
    assertFalse(this.trainer.getModel().classify(dataset.viewColumn(3)));
    assertTrue(this.trainer.getModel().classify(dataset.viewColumn(0)));
  }


}

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


    for (int m = low + 1; m <= high - 1; m++) {


      // Scale column.


      Vector hColumn = hessenBerg.viewColumn(m - 1).viewPart(m, high - m + 1);
      double scale = hColumn.norm(1);


      if (scale != 0.0) {
        // Compute Householder transformation.

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