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Competitive learning for binary valued data

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We propose a new approach for using online competitive learning on binary data. The usual Euclidean distance is replaced by binary distance measures, which take possible asymmetries of binary data into account and therefore provide a "different point of view" for looking at the data. The method is demonstrated on two artificial examples and applied on tourist marketing research data. (author's abstract) ; Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

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Friedrich Leisch, Andreas Weingessel, Evgenia Dimitriadou

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