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EnglishIn 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.
| Data di pubblicazione: | 1990 |
| Titolo: | A PARTITION TYPE METHOD FOR CLUSTERING MIXED DATA |
| Autori: | |
| Citazione: | CHIODI M (1990). A PARTITION TYPE METHOD FOR CLUSTERING MIXED DATA. STATISTICA APPLICATA, 2, 135-147. |
| Rivista: | |
| 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. |
| Settore Scientifico Disciplinare: | Settore SECS-S/01 - Statistica |
| Appare nelle tipologie: | 1.01 Articolo in rivista |
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