Package ac.essex.ooechs.kmeans

Provides a basic implementation of the K Means Clustering Algorithm.

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          Description

Class Summary
Centroid A Centroid is a position in N dimensional space, supposedly in the center of a cluster of points.
ClusterClass A basic class object with an ID and a name that allows some class information to be attached to each centroid.
DataPoint This datastructure represents a point of training data in the k means clustering scenario.
KMeansAlgorithm An implementation of the K means clustering algorith, which attempts to find the centroids assumed to be at the center of spherical clusters of points in n dimensional feature space.
KMeansSolution A utility class that allows the output of the K means clusterer to be tested on training or unseen data.
Position Represents a position in n dimensional feature space.
 

Package ac.essex.ooechs.kmeans Description

Provides a basic implementation of the K Means Clustering Algorithm.