Correspondence analysis and 2-way clustering
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...
| Autores: | , , |
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| Formato: | artículo |
| Fecha de publicación: | 2005 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099/3759 |
| Acesso em linha: | https://hdl.handle.net/2099/3759 |
| Access Level: | acceso abierto |
| Palavra-chave: | Multivariate analysis Anàlisi multivariable Classificació AMS::62 Statistics::62H Multivariate analysis |
| Resumo: | 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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