Package smile.clustering.linkage

Class WardLinkage

java.lang.Object

smile.clustering.linkage.Linkage

smile.clustering.linkage.WardLinkage

public class WardLinkage
extends Linkage

Ward's linkage. Ward's linkage follows the analysis of variance approach The dissimilarity between two clusters is computed as the increase in the "error sum of squares" (ESS) after fusing two clusters into a single cluster. Ward's Method seeks to choose the successive clustering steps to minimize the increase in ESS at each step. Note that it is only valid for Euclidean distance based proximity matrix.

Constructor Summary

Constructors

Constructor	Description
WardLinkage(double[][] proximity)	Constructor.
WardLinkage(int size, float[] proximity)	Constructor.

Method Summary

Modifier and Type	Method	Description
void	merge(int i, int j)	Merges two clusters into one and update the proximity matrix.
static WardLinkage	of(double[][] data)	Computes the proximity and the linkage.
static <T> WardLinkage	of(T[] data, Distance<T> distance)	Computes the proximity and the linkage.
String	toString()

Methods inherited from class smile.clustering.linkage.Linkage

d, proximity, proximity, size

Methods inherited from class java.lang.Object

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

Constructor Details

WardLinkage

public WardLinkage(double[][] proximity)

Constructor.

Parameters:

proximity - the proximity matrix. Only the lower half will be referred.

WardLinkage

public WardLinkage(int size,
 float[] proximity)

Constructor. Initialize the linkage with the lower triangular proximity matrix.

Parameters:

size - the data size.

proximity - the column-wise linearized proximity matrix that stores only the lower half. The length of proximity should be size * (size+1) / 2. To save space, Linkage will use this argument directly without copy. The elements may be modified.

Method Details

of

public static WardLinkage of(double[][] data)

Computes the proximity and the linkage.

Parameters:

data - the data points.

Returns:

the linkage.

of

public static <T> WardLinkage of(T[] data,
 Distance<T> distance)

Computes the proximity and the linkage.

Type Parameters:

T - the data type of points.

Parameters:

data - the data points.

distance - the distance function.

Returns:

the linkage.

toString

public String toString()

Overrides:

toString in class Object

merge

public void merge(int i,
 int j)

Description copied from class: Linkage

Merges two clusters into one and update the proximity matrix.

Specified by:

merge in class Linkage

Parameters:

i - cluster id.

j - cluster id.