On α-divergence based nonnegative matrix factorization for clustering cancer gene expression data

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摘要

ObjectiveNonnegative matrix factorization (NMF) has been proven to be a powerful clustering method. Recently Cichocki and coauthors have proposed a family of new algorithms based on the α-divergence for NMF. However, it is an open problem to choose an optimal α.

论文关键词：α-Divergence,Nonnegative matrix factorization,Gene expression data,Clustering

论文评审过程：Received 3 August 2007, Revised 13 May 2008, Accepted 13 May 2008, Available online 3 July 2008.

论文官网地址：https://doi.org/10.1016/j.artmed.2008.05.001