Two-way classification of a data table with non negative entries: The role of the χ 2 distance and Correspondence Analysis

  1. Ciampi, A. 1
  2. Dyachenko, A. 4
  3. Gonzalez-Marcos, A. 2
  4. Lechevallier, Y. 3
  1. 1 McGill University
    info

    McGill University

    Montreal, Canadá

    ROR https://ror.org/01pxwe438

  2. 2 Universidad de León
    info

    Universidad de León

    León, España

    ROR https://ror.org/02tzt0b78

  3. 3 INRIA, Rocquencourt, France
  4. 4 St. Mary's Research Center, St. Mary's Hospital, Montreal, QC, Canada
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Revista:
Communications in Statistics Part B: Simulation and Computation

ISSN: 0361-0918

Año de publicación: 2012

Volumen: 41

Número: 7

Páginas: 1006-1022

Tipo: Artículo

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DOI: 10.1080/03610918.2012.625772 SCOPUS: 2-s2.0-84862875406 GOOGLE SCHOLAR

Otras publicaciones en: Communications in Statistics Part B: Simulation and Computation

Resumen

We developed an approach to two-way classification based on the χ 2 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. Copyright © Taylor & Francis Group, LLC.