Abstract
The proportional membership model forfuzzy clustering (FCPM) [11] proposes amodel of how data are generated from acluster structure to be identi...ed. Dueto some restrictions of FCPM to recovercluster structures in data that havebeen generated di¤erently from what theFCPM model suggests, we further relaxthe rigid structure of the alternatingminimization algorithm for FCPM criteriato the so called alternating clusterestimation (ACE) [14]. In ACE,formulas for recalculation of the membershipand prototype functions fromeach other are directly de...ned by theuser. More speci...cally, in our approachthe fuzzy c-means prototype functionis combined with the FCPM proportionalmembership in the FCPM-AE algorithm.Preliminary experiments comparingthe FCPM-AE with the fuzzy cmeans(FCM) algorithm lead us to advancethat the proportional membershipis more discriminating than the FCMdistance membership.
Original language | English |
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Title of host publication | Information Processing and Management of Uncertainty in Knowledge-based Systems |
Subtitle of host publication | Proceedings : Eighth International Conference, IPMU, Madrid, July 3-7, 2000 |
Publisher | Universidad Politécnica de Madrid |
Pages | 1977-1981 |
Number of pages | 5 |
Volume | 1 |
Edition | 1 |
ISBN (Print) | 84-95479-02-8, 84-95479-03-6 |
Publication status | Published - 2000 |
Event | 8th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems(IPMU'00) - Madrid, Spain Duration: 3 Jul 2000 → 7 Jul 2000 |
Conference
Conference | 8th International Conference on Information Processing and Management of Uncertainty in Knowledge-based Systems(IPMU'00) |
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Abbreviated title | IPMU'00 |
Country/Territory | Spain |
City | Madrid |
Period | 3/07/00 → 7/07/00 |
Keywords
- Fuzzy clustering
- prototype
- proportional membership
- alternating optimization
- alternating cluster estimation