Geography of Di.erences between Two Classes of Data
Lecture notes in computer sciencePublished 1 January 2002
Jinyan Li, Limsoon Wong
Citations23
SJR quartileQ2
SJR score0.35
SNIP0.55
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TL;DR
Easily comprehensible ways of capturing main differences between two classes of data are investigated and a new method is proposed to classify testing samples that is competitive to several state-of-the-art algorithms.
Abstract
Easily comprehensible ways of capturing main differences between two classes of data are investigated in this paper. In addition to examining individual di.erences, we also consider their neighbourhood. The new concepts are applied to three gene expression datasets to discover diagnostic gene groups. Based on the idea of prediction by collective likelihoods (PCL), a new method is proposed to classify testing samples. Its performance is competitive to several state-of-the-art algorithms.
Keywords
Computer ScienceBiochemistry, Genetics and Molecular Biology
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