org.metaqtl.algo
Class HClustAlgorithm

java.lang.Object
  org.metaqtl.algo.HClustAlgorithm

public class HClustAlgorithm
extends java.lang.Object

This class implements stantard agglomerative hierarchical clustering methods.

Field Summary

static int	CENTROID_METHOD Centroid method
static int	METHOD A global variable to control the custering method.
static int	WARD_METHOD Ward method

Constructor Summary

HClustAlgorithm()

Method Summary

static Tree	CentroidMethod(double[] x, double[] sd) This method performs a hierarchical clustering of the given data points using a centroid method based on the mahalanobis distance.
static Tree	run(double[] x, double[] sd) This method performs a agglomerative clustering of the given data points where x is the vector of observed values and sd the vector of their standard deviations.
static Tree	WardMethod(double[] x, double[] sd) This method performs a hierarchical clustering of the given data points using the Ward's method.

Methods inherited from class java.lang.Object

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

Field Detail

CENTROID_METHOD

public static final int CENTROID_METHOD

Centroid method

See Also:

Constant Field Values

WARD_METHOD

public static final int WARD_METHOD

Ward method

See Also:

Constant Field Values

METHOD

public static int METHOD

A global variable to control the custering method.

Constructor Detail

HClustAlgorithm

public HClustAlgorithm()

Method Detail

run

public static Tree run(double[] x,
                       double[] sd)

This method performs a agglomerative clustering of the given data points where x is the vector of observed values and sd the vector of their standard deviations. It returns an array of TreeNode which represents the hierarchical clustering.

Parameters:

x - the vector of data points.

sd - the vector of standard deviations.

Returns:

the tree which represents the hierarchical clustering.

CentroidMethod

public static Tree CentroidMethod(double[] x,
                                  double[] sd)

This method performs a hierarchical clustering of the given data points using a centroid method based on the mahalanobis distance.

Parameters:

x - the vector of data points.

sd - the vector of standard deviations.

Returns:

the tree which represents the hierarchical clustering.

WardMethod

public static Tree WardMethod(double[] x,
                              double[] sd)

This method performs a hierarchical clustering of the given data points using the Ward's method.

Parameters:

x - the vector of data points.

sd - the vector of standard deviations.

Returns:

the tree which represents the hierarchical clustering.