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A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets

Shen, Zixiao; Chen, Xin; Garibaldi, Jonathan M.

Authors

Zixiao Shen

XIN CHEN XIN.CHEN@NOTTINGHAM.AC.UK
Assistant Professor



Abstract

In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fuzzy sets generation using bootstrap, weighted combination of fuzzy sets and feature ranking based on defuzzification. We implemented the proposed method by combining four state-of-the-art feature selection methods and evaluated the performance based on three publicly available biomedical datasets using fivefold cross validation. Based on the feature selection results, our proposed method produced comparable (if not better) classification accuracies to the best of the individual feature selection methods for all evaluated datasets. More importantly, we also applied standard deviation and Pearson's correlation to measure the stability of the methods. Remarkably, our combination method achieved significantly higher stability than the four individual methods when variations and size reductions were introduced to the datasets.

Citation

Shen, Z., Chen, X., & Garibaldi, J. M. (2019). A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)https://doi.org/10.1109/fuzz-ieee.2019.8858890

Conference Name 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Start Date Jun 23, 2019
End Date Jun 26, 2019
Acceptance Date Mar 4, 2019
Online Publication Date Oct 10, 2019
Publication Date 2019-06
Deposit Date Nov 5, 2019
Publisher Institute of Electrical and Electronics Engineers
Book Title 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
ISBN 9781538617281
DOI https://doi.org/10.1109/fuzz-ieee.2019.8858890
Public URL https://nottingham-repository.worktribe.com/output/3062771
Publisher URL https://ieeexplore.ieee.org/document/8858890
Additional Information © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.