Abstract
We develop a method of grouping (clustering) variables based on fuzzy equivalence relations. We first compute the pairwise relationship (correlation) matrix between the variables and transform the matrix into a fuzzy compatibility relation. Then a fuzzy equivalence relation is constructed by computing the transitive closure of the compatibility relation. Finally, by taking all appropriate α-cuts, we obtain a hierarchical type of variable clustering. As examples, we use the proposed method first as a variable clustering tool in a regression model and secondly as a new way of performing factor analysis.
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Acknowledgments
This research was financially supported through the university scholarship for doctoral students (KE 81516) in the section of Mathematics and Informatics, Department of Civil Engineering. The scholarship is awarded by the Research Committee of the Democritus University of Thrace.
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Adjenughwure, K.S., Botzoris, G.N., Papadopoulos, B.K. (2015). Clustering Variables Based on Fuzzy Equivalence Relations. In: Gil-Aluja, J., Terceño-Gómez, A., Ferrer-Comalat, J., Merigó-Lindahl, J., Linares-Mustarós, S. (eds) Scientific Methods for the Treatment of Uncertainty in Social Sciences. Advances in Intelligent Systems and Computing, vol 377. Springer, Cham. https://doi.org/10.1007/978-3-319-19704-3_18
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DOI: https://doi.org/10.1007/978-3-319-19704-3_18
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