Speeding-Up the K-Means Clustering Method: A Prototype Based Approach
The paper is about speeding-up the k-means clustering method which processes the data in a faster pace, but produces the same clustering result as the k-means method. We present a prototype based method for this where prototypes are derived using the leaders clustering method. Along with prototypes called leaders some additional information is also preserved which enables in deriving the k means. Experimental study is done to compare the proposed method with recent similar methods which are mainly based on building an index over the data-set.
KeywordsCluster Method Leader Method Density Base Cluster Method Partition Base Method Pattern Recognition Research
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