gov.sandia.cognition.math

Interface DivergenceFunction<FirstType,SecondType>

Type Parameters:

FirstType - First class to consider

SecondType - Second class to consider

All Known Subinterfaces:

ClusterDivergenceFunction<ClusterType,DataType>, ClusterToClusterDivergenceFunction<ClusterType,DataType>, Metric<EvaluatedType>, Semimetric<InputType>

All Known Implementing Classes:

AbstractClusterToClusterDivergenceFunction, CentroidClusterDivergenceFunction, ChebyshevDistanceMetric, ClusterCentroidDivergenceFunction, ClusterCompleteLinkDivergenceFunction, ClusterMeanLinkDivergenceFunction, ClusterSingleLinkDivergenceFunction, CosineDistanceMetric, EuclideanDistanceMetric, EuclideanDistanceSquaredMetric, GaussianClusterDivergenceFunction, IdentityDistanceMetric, KernelDistanceMetric, ManhattanDistanceMetric, MinkowskiDistanceMetric, WeightedEuclideanDistanceMetric

@CodeReview(reviewer="Kevin R. Dixon",date="2008-02-26",changesNeeded=false,comments="Looks good.") @CodeReview(reviewer="Jonathan McClain",date="2006-05-16",changesNeeded=false,comments="Looks good.")
public interface DivergenceFunction<FirstType,SecondType>

The DivergenceFunction class defines the functionality of something that computes the divergence between two objects. A divergence function should have the following properties: g(x, y) >= 0 g(x, x) == 0 It is recommended that an DivergenceFunction implement CloneableSerializable, though it is not required.

Since:

1.0

Author:

Justin Basilico, Kevin R. Dixon

Method Summary

Modifier and Type	Method and Description
double	evaluate(FirstType first, SecondType second) Evaluates the divergence between the two given objects.

Method Detail

evaluate

double evaluate(FirstType first,
                SecondType second)

Evaluates the divergence between the two given objects.

Parameters:

first - The first object.

second - The second object.

Returns:

The divergence between the objects.