Similarity Measures Based on a Fuzzy Set Model and Application to Hierarchical Clustering
- 1 May 1986
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Systems, Man, and Cybernetics
- Vol. 16 (3) , 479-482
- https://doi.org/10.1109/TSMC.1986.4308983
Abstract
A fuzzy set model for generalizing similarity measures of binary characters for numerical classification is proposed. A set-theoretical model representation is given for well-known similarities of binary characters in mathematical taxonomy. Then a fuzzy extension of the set-theoretical model leads to generalizations of these similarities. Moreover an algorithm of hierarchical agglomerative clustering is developed in which similarity between a pair of clusters is calculated by referring to the model. An example based on psychological association is shown.Keywords
This publication has 5 references indexed in Scilit:
- Directed Graph Representations of Association Structures: A Systematic ApproachIEEE Transactions on Systems, Man, and Cybernetics, 1986
- A model for the measurement of membership and the consequences of its empirical implementationFuzzy Sets and Systems, 1984
- Pattern Recognition with Fuzzy Objective Function AlgorithmsPublished by Springer Nature ,1981
- Applications of Fuzzy Sets to Systems AnalysisPublished by Springer Nature ,1975
- Fuzzy setsInformation and Control, 1965