A New Approach for Cancer Classification using Microarray Gene Expression Data

T.D. Pham, M. Brandl, and D. Beck (Australia)


Microarray data analysis, pattern recognition, vector quan tization, fuzzy declustering.


We propose in this paper a new approach for classifica tion of cancers using microarray gene expression data. The proposed method adopts the concept of fuzzy declustering strategy for vector quantization algorithm. The notion of fuzzy partition entropy is coupled with the distortion mea sures for classifying spectral features of microarray data. Experimental results obtained from real datasets demon strate the effective performance of the proposed approach.

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