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) |
|---|---|
| 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 |
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Keywords
- Lagrangian relaxation
- cluster analysis
- combinatorial data analysis
- heuristics
- p-median problem
ASJC Scopus subject areas
- Psychology (miscellaneous)
Cite this
The p-Median Model as a Tool for Clustering Psychological Data. / Köhn, Hans Friedrich; Steinley, Douglas; Brusco, Michael J.
In: Psychological Methods, Vol. 15, No. 1, 03.2010, p. 87-95.Research output: Contribution to journal › Article
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TY - JOUR
T1 - The p-Median Model as a Tool for Clustering Psychological Data
AU - Köhn, Hans Friedrich
AU - Steinley, Douglas
AU - Brusco, Michael J.
PY - 2010/3
Y1 - 2010/3
N2 - 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.
AB - 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.
KW - Lagrangian relaxation
KW - cluster analysis
KW - combinatorial data analysis
KW - heuristics
KW - p-median problem
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UR - http://www.scopus.com/inward/citedby.url?scp=77949646469&partnerID=8YFLogxK
U2 - 10.1037/a0018535
DO - 10.1037/a0018535
M3 - Article
C2 - 20230105
AN - SCOPUS:77949646469
VL - 15
SP - 87
EP - 95
JO - Psychological Methods
JF - Psychological Methods
SN - 1082-989X
IS - 1
ER -