An Efficient K-Means with Microarray Gene Expression Using Affinity Propagation for Cancer Dataset

G. Baskar, D. Napoleon

Abstract


Clustering is an important topic in data mining research. Clustering attributes, the search dimension of a data mining algorithm .Kmeans
algorithm is one of the basic and most simple partitioning clustering techniques. The main strength of the algorithm is that it can quickly
determine Clustering’s of the same point set for many values of k This paper presents an clustering method which is able to group genes based
on their interdependence so as to mine meaningful patterns from the gene expression data on leukemia dataset .Here the algorithm used is
Efficient K-Means, X-Means, and Affinity Propagation.

 


Keyword: Data Mining, Efficient K-Means, X-Means, Affinity Propagation, leukemia.


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DOI: https://doi.org/10.26483/ijarcs.v2i3.461

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