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. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Sarma, T. H., & Viswanath, P. (2009). Speeding-up the K-means clustering method: A prototype based approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5909 LNCS, pp. 56–61). https://doi.org/10.1007/978-3-642-11164-8_10
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