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Erschienen in:
2009 | OriginalPaper | Buchkapitel
Making Archetypal Analysis Practical
verfasst von : Christian Bauckhage, Christian Thurau
Erschienen in: Pattern Recognition
Verlag: Springer Berlin Heidelberg
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Archetypal analysis represents the members of a set of multivariate data as a convex combination of extremal points of the data. It allows for dimensionality reduction and clustering and is particularly useful whenever the data are superpositions of basic entities. However, since its computation costs grow quadratically with the number of data points, the original algorithm hardly applies to modern pattern recognition or data mining settings. In this paper, we introduce ways of notably accelerating archetypal analysis. Our experiments are the first successful application of the technique to large scale data analysis problems.