Package org.ddogleg.clustering.kmeans

Interface InitializeKMeans<P>

All Known Implementing Classes:

InitializePlusPlus, InitializePlusPlus_MT, InitializeStandard

public interface InitializeKMeans<P>

Selects the initial cluster positions for k-means

Method Summary

Modifier and Type	Method	Description
void	initialize(PointDistance<P> distance, long randomSeed)	Initializes internal data structures.
InitializeKMeans<P>	newInstanceThread()	Creates a new instance which has the same configuration and can be run in parallel.
void	selectSeeds(LArrayAccessor<P> points, int requestedSeeds, DogArray<P> selectedSeeds)	Given the a set of points, select a set of seeds to initialize k-means from.

Method Details

initialize

void initialize(PointDistance<P> distance,
 long randomSeed)

Initializes internal data structures. Must be called first.

Parameters:

distance - Distance function between two points

randomSeed - Seed for any random number generators used internally.

selectSeeds

void selectSeeds(LArrayAccessor<P> points,
 int requestedSeeds,
 DogArray<P> selectedSeeds)

Given the a set of points, select a set of seeds to initialize k-means from.

• How duplicate points are handled isn't specified. It could result in two seeds having the same value or the number of selected seeds being less that the requested amount
• If the number of points is less than the number of seeds requested it will at most select one seed for each point

*

Parameters:

points - (Input) Set of points which is to be clustered.

requestedSeeds - (Input) Number of seeds it will attempt to select. See above for exceptions.

selectedSeeds - (Output) Storage for selected seeds. They will be copied into it.

newInstanceThread

InitializeKMeans<P> newInstanceThread()

Creates a new instance which has the same configuration and can be run in parallel. Some components can be shared as long as they are read only and thread safe.