Clustering Gene Expression for Colon and Leukemia Dataset Using Affinity Propagation

D. Napoleon, G. Baskar

Abstract


The most prominent and widely used clustering algorithm is Lloyd’s algorithm sometimes also referred to as the k-means algorithm.
The k-means algorithm is one of the most widely used methods to partition a Dataset into groups of patterns. The main strength of the algorithm
is that it can quickly determine Clustering’s of the same point set for many values of k. However, the k-means method converges to one of many
local minima. And it is known that, the final result depends on the initial starting points. We introduce an global k-means, x-means and affinity
propagation. our experimental results show that, good initial starting points lead to improved solution

 

 


Keyword: Data mining, Global k-means, x-means, Affinity propagation.


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DOI: https://doi.org/10.26483/ijarcs.v2i1.335

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