Fuzzy clustering in classification using weighted features

Authors:
Lourenço P. C. Bandeira;João M. C. Sousa;Uzay Kaymak
Affiliations:
Technical University of Lisbon, Instituto Superior Técnico, Dept. of Mechanical Engineering, GCAR/IDMEC, Lisbon, Portugal;Technical University of Lisbon, Instituto Superior Técnico, Dept. of Mechanical Engineering, GCAR/IDMEC, Lisbon, Portugal;Erasmus University of Rotterdam, Faculty of Economics, Rotterdam, the Netherlands
Venue:
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Year:
2003

Citing 2
Cited 0

Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy clustering with volume prototypes and adaptive cluster merging

IEEE Transactions on Fuzzy Systems

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Abstract

This paper proposes a fuzzy classification/regression method based on an extension of classical fuzzy clustering algorithms, by weighting the features during cluster estimation. By translating the importance of each feature using weights, the classifier can lead to better results. The proposed method is applied to target selection, where the goal is to maximize profit obtained from the clients. A real-world application shows the effectiveness of the proposed approach.