Package elki.clustering.hierarchical.birch

Class ClusteringFeature

java.lang.Object

elki.clustering.hierarchical.birch.ClusteringFeature

public class ClusteringFeature
extends java.lang.Object

Clustering Feature of BIRCH

Since:

0.7.5

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
(package private) double[]	ls	Linear sum.
(package private) int	n	Number of objects
(package private) double	ss	Sum of squares (see original thesis, this is a scalar).

Constructor Summary

Constructors

Constructor	Description
ClusteringFeature(int dimensionality)	Constructor.

Method Summary

Modifier and Type	Method	Description
protected void	addToStatistics(ClusteringFeature other)	Merge an other clustering features.
protected void	addToStatistics(NumberVector nv)	Add a number vector to the current node.
double	centroid(int i)	Centroid value in dimension i.
int	getDimensionality()	Dimensionality of the clustering feature.
protected void	resetStatistics()	Reset the CF to zero.
static double	sumOfSquares(NumberVector v)	Compute the sum of squares of a vector.
double	sumOfSquaresOfSums()	Sum over all dimensions of squares of linear sums.
double	sumOfSumOfSquares()	Sum over all dimensions of sums of squares.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

n

int n

Number of objects

ls

double[] ls

Linear sum.

ss

double ss

Sum of squares (see original thesis, this is a scalar).

Constructor Detail

ClusteringFeature

public ClusteringFeature(int dimensionality)

Constructor.

Parameters:

dimensionality - Dimensionality

Method Detail

addToStatistics

protected void addToStatistics(NumberVector nv)

Add a number vector to the current node.

Parameters:

nv - Vector to add

addToStatistics

protected void addToStatistics(ClusteringFeature other)

Merge an other clustering features.

Parameters:

other - Other CF

resetStatistics

protected void resetStatistics()

Reset the CF to zero. For use in splitting.

centroid

public double centroid(int i)

Centroid value in dimension i.

Parameters:

i - Dimension

Returns:

Average, or zero

sumOfSumOfSquares

public double sumOfSumOfSquares()

Sum over all dimensions of sums of squares.

Returns:

Sum of SS

sumOfSquaresOfSums

public double sumOfSquaresOfSums()

Sum over all dimensions of squares of linear sums.

Returns:

Sum of LS

getDimensionality

public int getDimensionality()

Dimensionality of the clustering feature.

Returns:

Dimensionality

sumOfSquares

public static double sumOfSquares(NumberVector v)

Compute the sum of squares of a vector.

Parameters:

v - Vector

Returns:

Sum of squares