Class EMProjectedClustering
- java.lang.Object
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- moa.clusterers.outliers.AnyOut.util.EMProjectedClustering
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public class EMProjectedClustering extends Object
Implements clustering via Expectation Maximization but return a clear partitioning of the data, i.e. a point belongs to only one cluster (the most probable)- Author:
- kranen
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Constructor Summary
Constructors Constructor Description EMProjectedClustering()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description int[][]
getEMClusteringVariances(double[][] pointArray, int k)
Performs an EM clustering on the provided data set !! Only the variances are calculated and used for point assignments ! !!! the number k' of returned clusters might be smaller than k !!!int[][]
getEMClusteringVariancesBestChoice(double[][] pointArray, int k, int nrOfChoices)
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Method Detail
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getEMClusteringVariances
public int[][] getEMClusteringVariances(double[][] pointArray, int k)
Performs an EM clustering on the provided data set !! Only the variances are calculated and used for point assignments ! !!! the number k' of returned clusters might be smaller than k !!!- Parameters:
pointArray
- the data set as an array[n][d] of n points with d dimensionsk
- the number of requested partitions (!might return less)- Returns:
- a mapping int[n][k'] of the n given points to the k' resulting clusters
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getEMClusteringVariancesBestChoice
public int[][] getEMClusteringVariancesBestChoice(double[][] pointArray, int k, int nrOfChoices)
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