Recognition task with feature selection and weighted majority voting based on interval-valued fuzzy sets

Authors:
Robert Burduk
Affiliations:
Department of Systems and Computer Networks, Wroclaw University of Technology, Wroclaw, Poland
Venue:
ICCCI'12 Proceedings of the 4th international conference on Computational Collective Intelligence: technologies and applications - Volume Part I
Year:
2012

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Abstract

This paper presents the recognition algorithm with random selection of features. In the proposed procedure of classification the choice of weights is one of the main problems. In this paper we propose the weighted majority vote rule in which weights are represented by interval-valued fuzzy set (IVFS). In our approach the weights have a lower and upper membership function. The described algorithm was tested on one data set from UCI repository. The obtained results are compared with the most popular majority vote and the weighted majority vote rule.