Interpretability indices for hierarchical fuzzy systems

Razak, T. R.; Garibaldi, J. M.; Wagner, C.; Pourabdollah, A.; Soria, D.

Abstract

© 2017 IEEE. Hierarchical fuzzy systems (HFSs) have been shown to have the potential to improve interpretability of fuzzy logic systems (FLSs). In recent years, a variety of indices have been proposed to measure the interpretability of FLSs such as the Nauck index and Fuzzy index. However, interpretability indices associated with HFSs have not so far been discussed. The structure of HFSs, with multiple layers, subsystems, and varied topologies, is the main challenge in constructing interpretability indices for HFSs. Thus, the comparison of interpretability between FLSs and HFSs - even at the index level - is still subject to open discussion. This paper begins to address these challenges by introducing extensions to the FLS Nauck and Fuzzy interpretability indices for HFSs. Using the proposed indices, we explore the concept of interpretability in relation to the different structures in FLSs and HFSs. Initial experiments on benchmark datasets show that based on the proposed indices, HFSs with equivalent function to FLSs produce higher indices, i.e. are more interpretable than their corresponding FLSs.

Citation

Razak, T. R., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (2017). Interpretability indices for hierarchical fuzzy systems. In Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1-6). https://doi.org/10.1109/FUZZ-IEEE.2017.8015616

• Conference Name: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• Conference Location: Naples, Italy
• Start Date: Jul 9, 2017
• End Date: Jul 12, 2017
• Acceptance Date: Mar 14, 2017
• Online Publication Date: Aug 24, 2017
• Publication Date: 2017-07
• Deposit Date: Apr 26, 2017
• Publicly Available Date: Jul 31, 2017
• Journal: Proceedings of the IEEE International Fuzzy Systems Conference
• Electronic ISSN: 1544-5615
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 1-6
• Series ISSN: 1558-4739
• Book Title: Proceedings of the 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
• ISBN: 978-1-5090-6035-1
• DOI: https://doi.org/10.1109/FUZZ-IEEE.2017.8015616
• Public URL: https://nottingham-repository.worktribe.com/output/878850
• Publisher URL: http://ieeexplore.ieee.org/document/8015616/
• Additional Information: Published in Proceedings of the IEEE International Fuzzy Systems Conference. IEEE, 2017. ISBN: 9781509060344. DOI: 10.1109/FUZZ-IEEE.2017.8015616