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- W2065004085 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." @default.
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- W2065004085 date "2002-01-01" @default.
- W2065004085 modified "2023-09-25" @default.
- W2065004085 title "Geography of Di.erences between Two Classes of Data" @default.
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- W2065004085 doi "https://doi.org/10.1007/3-540-45681-3_27" @default.
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