Correspondence analysis and 2-way clustering
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Antonio Ciampi [1]
;
Ana González Marcos
[2]
;
Manuel Castejón Limas
[2]
-
[1] McGill University
McGill University
Canadá
-
[2] Universidad de León
Universidad de León
León, España
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- Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 29, Nº. 1, 2005, págs. 27-41
- Idioma: inglés
- Títulos paralelos:
- Análisis de correspondencias y agregación de doble entrada
- Enlaces
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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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