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See:
Description
Class Summary | |
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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. |
Provides a basic implementation of the K Means Clustering Algorithm.
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