Abstract
The p-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around exemplars, that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of p-median clustering are virtually unavailable in the popular social and behavioral science statistical software packages. We present p-median clustering, including a detailed description of its mechanics and a discussion of available software programs and their capabilities. Application to a complex structured data set on the perception of food items illustrates p-median clustering.
Original language | English (US) |
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Pages (from-to) | 87-95 |
Number of pages | 9 |
Journal | Psychological Methods |
Volume | 15 |
Issue number | 1 |
DOIs | |
State | Published - Mar 2010 |
Externally published | Yes |
Keywords
- Lagrangian relaxation
- cluster analysis
- combinatorial data analysis
- heuristics
- p-median problem
ASJC Scopus subject areas
- Psychology (miscellaneous)