Title :
A Combination Scheme for Fuzzy Partitions Based on Fuzzy Majority Voting Rule
Author_Institution :
Dept. of Math. & Comput. Sci., Guang Dong Univ. of Bus. Studies, Guangzhou
Abstract :
This paper propose a combination model of fuzzy partitions with the same number of clusters by generalizing the traditional majority voting rule to fuzzy majority voting rule and a class matching algorithm based on k nearest neighbours (KNN) to establish the correspondence among classes of component fuzzy partitions. The comparisons between our combination model and other two methods over real-world data sets show that our combination method is a little better than the other two.
Keywords :
fuzzy set theory; pattern matching; class matching algorithm; combination model; component fuzzy partitions; fuzzy majority voting rule; k nearest neighbours; Business communication; Clustering algorithms; Computer networks; Fuzzy set theory; Fuzzy sets; Mathematical model; Mathematics; Partitioning algorithms; Voting; Wireless communication; combination of fuzzy partitions; evaluation of fuzzy partition; fuzzy majority voting rule; fuzzy vote;
Conference_Titel :
Networks Security, Wireless Communications and Trusted Computing, 2009. NSWCTC '09. International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-1-4244-4223-2
DOI :
10.1109/NSWCTC.2009.251