Correspondence analysis and 2-way clustering

  1. Ciampi, Antonio 1
  2. González Marcos, Ana 2
  3. Castejón Limas, Manuel 2
  1. 1 McGill University, Montreal, Canada, Department of Epidemiology and Statistics, Canada
  2. 2 Universidad de León
    info

    Universidad de León

    León, España

    ROR https://ror.org/02tzt0b78

Revista:
Sort: Statistics and Operations Research Transactions

ISSN: 1696-2281

Año de publicación: 2005

Volumen: 29

Número: 1

Páginas: 27-41

Tipo: Artículo

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Otras publicaciones en: Sort: Statistics and Operations Research Transactions

Resumen

Correspondence analysis followed by clustering of both rows and columns of a data matrix is proposed as an approach to two-way clustering. The novelty of this contribution consists of: i) proposing a simple method for the selecting of the number of axes; ii) visualizing the data matrix as is done in micro-array analysis; iii) enhancing this representation by emphasizing those variables and those individuals which are 'well represented' in the subspace of the chosen axes. The approach is applied to a 'traditional' clustering problem: the classification of a group of psychiatric patients.

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Fuente de los datos: Dialnet