A proposal of an extended version of the HINoV method for the iden-
tification of the noisy variables (Carmone et al ) for nonmetric, mixed, and
symbolic interval data is presented in this paper. Proposed modifications are eval-
uated on simulated data from a variety of models. The models contain the known
structure of clusters. In addition, the models contain a different number of noisy
(irrelevant) variables added to obscure the underlying structure to be recovered.