smile.clustering.linkage

Class SingleLinkage

java.lang.Object

smile.clustering.linkage.Linkage

smile.clustering.linkage.SingleLinkage

public class SingleLinkage
extends Linkage

Single linkage. The distance between groups is defined as the distance between the closest pair of objects, one from each group. A drawback of this method is the so-called chaining phenomenon: clusters may be forced together due to single elements being close to each other, even though many of the elements in each cluster may be very distant to each other.

Single linkage clustering is essentially the same as Kruskal's algorithm for minimum spanning trees. However, in single linkage clustering, the order in which clusters are formed is important, while for minimum spanning trees what matters is the set of pairs of points that form distances chosen by the algorithm.

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
void	merge(int i, int j) Merge two clusters into one and update the proximity matrix.
static SingleLinkage	of(double[][] data) Given a set of data, computes the proximity and then the linkage.
static <T> SingleLinkage	of(T[] data, smile.math.distance.Distance<T> distance) Given a set of data, computes the proximity and then the linkage.
java.lang.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 Detail

SingleLinkage

public SingleLinkage(double[][] proximity)

Constructor.

Parameters:

proximity - The proximity matrix to store the distance measure of dissimilarity. To save space, we only need the lower half of matrix.

SingleLinkage

public SingleLinkage(int size,
                     float[] proximity)

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

Parameters:

size - the data size.

proximity - 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 Detail

of

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

Given a set of data, computes the proximity and then the linkage.

of

public static <T> SingleLinkage of(T[] data,
                                   smile.math.distance.Distance<T> distance)

Given a set of data, computes the proximity and then the linkage.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

merge

public void merge(int i,
                  int j)

Description copied from class: Linkage

Merge two clusters into one and update the proximity matrix.

Specified by:

merge in class Linkage

Parameters:

i - cluster id.

j - cluster id.