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.
@article{urn:eudml:doc:40465,
title = {Correspondence analysis and two-way clustering.},
journal = {SORT},
volume = {29},
year = {2005},
pages = {27-42},
mrnumber = {MR2160535},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:40465}
}
Ciampi, Antonio; González Marcos, Ana; Castejón Limas, Manuel. Correspondence analysis and two-way clustering.. SORT, Tome 29 (2005) pp. 27-42. http://gdmltest.u-ga.fr/item/urn:eudml:doc:40465/