Abstract
Methodology is described for fitting a fuzzy consensus partition to a set of partitions of the same set of objects. Three models defining median partitions are described: two of them are obtained from a least-squares fit of a set of membership functions. and the third (proposed by Pittau and Vichi) is acquired from a least-squares fit of a set of joint membership functions. The models are illustrated by application to both a set of hard partitions and a set of fuzzy partitions and comparisons are made between them and an alternative approach to obtaining a consensus fuzzy partition proposed by Sate and Sate; a discussion is given of some interesting differences in the results.
| Original language | English |
|---|---|
| Pages (from-to) | 229-247 |
| Number of pages | 19 |
| Journal | Psychometrika |
| Volume | 66 |
| Publication status | Published - Jun 2001 |
Keywords
- classification
- cluster analysis
- consensus fuzzy partition
- membership function
- three-way data
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