Description: k-means clustering is a method of vector quantization, originally signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.
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kmeans\Centroid.java
......\Clustering.java
......\ComparisonFrame.java
......\DataPoint.java
......\EMCluster.java
......\EMFrame.java
......\HierarchicalClustering.java
......\HierarchicalFrame.java
......\JCA.java
......\KMeansFrame.java
......\Main.java
......\MainFrame.java
......\Preprocess.java
......\SOMCluster.java
......\SOMFrame.java
......\TermFrequency.java
kmeans
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