Correspondence analysis and 2-way clustering

• Antonio Ciampi ^[1] ; Ana González Marcos ^[2] ; Manuel Castejón Limas ^[2]
  1. [1] McGill University

     McGill University

     Canadá

     
  2. [2] Universidad de León

     Universidad de León

     León, España

     
• 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
  • Texto completo (pdf)
• 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.