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Microarray gene expression data is voluminous and very few genes in the dataset are informative for disease analysis. Selecting those genes from the whole dataset is a very challenging task. There are many optimization techniques used by the researchers for gene subset selection but none of them provides global optimal solution for all gene datasets. In the paper, we have proposed a strength pareto...
The estimation of the number of clusters (NC) is one of crucial problems in the cluster analysis of gene expression data. Most approaches available give their answers without the intuitive information about separable degrees between clusters. However, this information is useful for understanding cluster structures. To provide this information, we propose system evolution (SE) method to estimate NC...
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