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IJSTR >> Volume 8 - Issue 10, October 2019 Edition



International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616



Greedy Two Way K-Means Clustering For Optimal Coherent Triclsuter

[Full Text]

 

AUTHOR(S)

N. Narmadha, R. Rathipriya

 

KEYWORDS

Triclustering, Greedy Approach, Yeast Cell Cycle data, Gene expression data, Optimal Tricluster, 3D data,Correaltion

 

ABSTRACT

Generally, a grouping of the data can be classified as three ways i) Grouping of data in one dimension is called as clustering ii) Grouping of data in two-dimension is called as biclustering iii) Grouping of data in three-dimensional is called triclustering. Now- a -days, triclustering is the frequently used data mining technique for analysis of 3D gene expression data. A tricluster of a gene expression dataset is a subset of a gene which exhibits similar expression patterns with a subset of condition along with the time point. In this paper Greedy two way K- Means clustering algorithm for optimal coherent tricluster is performed over every time point. This algorithm is taken as seed to generate the tricluster to identify a coherent pattern based tricluster with high MCV and larger volume. The performance study is carried out to test the proposed algorithm. The results show that proposed algorithm identifies larger volume tricluster with high correlation among genes of 3D dataset.

 

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