Two-Way Classification of a Data Table with Non Negative Entries: The Role of the χ2 Distance and Correspondence Analysis

Abstract : We developed an approach to two-way classification based on the χ2 distance and Correspondence Analysis. We present, in particular, two classification algorithms: the first one operates a dimension reduction before applying clustering techniques to rows and columns. The second one, successively partitions the data matrix to extract several classification schemes rather than one. Applications to gene expression and web data are presented. The results are compared with an optimal partition algorithm.
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Communications in Statistics - Simulation and Computation, Taylor & Francis, 2012, 41 (7), pp.1006-1022. 〈10.1080/03610918.2012.625772〉
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https://hal.inria.fr/hal-00782454
Contributeur : Nathalie Gaudechoux <>
Soumis le : mardi 29 janvier 2013 - 17:23:35
Dernière modification le : jeudi 11 janvier 2018 - 16:57:43

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Antonio Ciampi, Alina Dyachenko, Ana Gonzalez-Marcos, Yves Lechevallier. Two-Way Classification of a Data Table with Non Negative Entries: The Role of the χ2 Distance and Correspondence Analysis. Communications in Statistics - Simulation and Computation, Taylor & Francis, 2012, 41 (7), pp.1006-1022. 〈10.1080/03610918.2012.625772〉. 〈hal-00782454〉

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