Description of individuals in ill-structured domains produces messy data matrices. In this context, automated classification requires the management of those kind of matrices. One of the features involved in clustering is the evaluation of distances between individuals. Then, a special function to calculate distances between individuals partially simultaneously described by qualitative and quantitative variables is required.
In this paper properties and details of the metrics used by Klass in this situation is presented - Klass is a clustering system oriented to the classification of ill-structured domains which implements an adapted version of the reciprocal neighbors algorithm; it also takes advantage of any additional information that an expert can provide about the target concepts.
@article{urn:eudml:doc:39112,
title = {Weighting quantitative and qualitative variables in clustering methods.},
journal = {Mathware and Soft Computing},
volume = {4},
year = {1997},
pages = {251-266},
language = {en},
url = {http://dml.mathdoc.fr/item/urn:eudml:doc:39112}
}
Gibert, Karina; Cortés, Ulises. Weighting quantitative and qualitative variables in clustering methods.. Mathware and Soft Computing, Tome 4 (1997) pp. 251-266. http://gdmltest.u-ga.fr/item/urn:eudml:doc:39112/