Microarray is a powerful technology for biological exploration which enables to simultaneously measure the level of activity of thousands genes in various cancer study . clustering is important data mining technique to extract useful information from various high dimensional datasets. A wide range of clustering algorithm is available and still in an open area of research k-Means algorithm is one of the basic and most simple partitioning clustering technique is given by Mac Queen in 1967. In this paper a sample weighting and efficient margin based sample weighting algorithm to improve the stability of feature selection. We proposed a weighted k-means to improve the cluster stability and presented an experimental evaluation of the proposed method, the experiment of microarray dataset show the feature selection algorithm such as SVM-RFE are more stable in gene selection.

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Feature Selection Classification Clustering Gene Expression Microarray