smile.validation

Class RandIndex

java.lang.Object

smile.validation.RandIndex

All Implemented Interfaces:

ClusterMeasure

public class RandIndex
extends java.lang.Object
implements ClusterMeasure

Rand Index. Rand index is defined as the number of pairs of objects that are either in the same group or in different groups in both partitions divided by the total number of pairs of objects. The Rand index lies between 0 and 1. When two partitions agree perfectly, the Rand index achieves the maximum value 1. A problem with Rand index is that the expected value of the Rand index between two random partitions is not a constant. This problem is corrected by the adjusted Rand index that assumes the generalized hyper-geometric distribution as the model of randomness. The adjusted Rand index has the maximum value 1, and its expected value is 0 in the case of random clusters. A larger adjusted Rand index means a higher agreement between two partitions. The adjusted Rand index is recommended for measuring agreement even when the partitions compared have different numbers of clusters.

Constructor Summary

Constructors

Constructor and Description
RandIndex()

Method Summary

Modifier and Type	Method and Description
double	measure(int[] y1, int[] y2) Returns an index to measure the quality of clustering.
java.lang.String	toString()

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

RandIndex

public RandIndex()

Method Detail

measure

public double measure(int[] y1,
                      int[] y2)

Description copied from interface: ClusterMeasure

Returns an index to measure the quality of clustering.

Specified by:

measure in interface ClusterMeasure

Parameters:

y1 - the cluster labels.

y2 - the alternative cluster labels.

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object