In this paper, we propose a method for clustering mixed data. The method is a nonhierarchical one, and deals simultaneously with variables of three main kinds: numerical, ordinal, and nominal. It is based on the minimization of a particular criterion f(G。) over all the partitions G。of n entities in m distinct clusters. The criterion is founded on a peculiar kind of internal standardized mean diversity of the entities, according to the three types of variables. The algorithm to get the best partition is also presented: it starts from a non-random choice of the first partition; the results are compared with those obtained by a random assignment to a first partition. In order to show the usefulness of the method and the performance of the algorithm on a large set of real data, an application to andrological mixed data is reported.

CHIODI M (1990). A PARTITION TYPE METHOD FOR CLUSTERING MIXED DATA. STATISTICA APPLICATA, 2, 135-147.

A PARTITION TYPE METHOD FOR CLUSTERING MIXED DATA

CHIODI M
Methodology
1990-01-01

Abstract

In this paper, we propose a method for clustering mixed data. The method is a nonhierarchical one, and deals simultaneously with variables of three main kinds: numerical, ordinal, and nominal. It is based on the minimization of a particular criterion f(G。) over all the partitions G。of n entities in m distinct clusters. The criterion is founded on a peculiar kind of internal standardized mean diversity of the entities, according to the three types of variables. The algorithm to get the best partition is also presented: it starts from a non-random choice of the first partition; the results are compared with those obtained by a random assignment to a first partition. In order to show the usefulness of the method and the performance of the algorithm on a large set of real data, an application to andrological mixed data is reported.
1990
Settore SECS-S/01 - Statistica
CHIODI M (1990). A PARTITION TYPE METHOD FOR CLUSTERING MIXED DATA. STATISTICA APPLICATA, 2, 135-147.
File in questo prodotto:
File Dimensione Formato  
RSA_mixedtype_clustering.pdf

Solo gestori archvio

Tipologia: Post-print
Dimensione 1.25 MB
Formato Adobe PDF
1.25 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/441457
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact