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Interpretability indices for hierarchical fuzzy systems

Razak, T.R.; Garibaldi, Jonathan M.; Wagner, Christian; Pourabdollah, Amir; Soria, Daniele

Authors

T.R. Razak

Jonathan M. Garibaldi

Christian Wagner

Amir Pourabdollah

Daniele Soria



Abstract

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.

Journal Proceedings of the IEEE International Fuzzy Systems Conference
Electronic ISSN 1544-5615
Peer Reviewed Peer Reviewed
APA6 Citation Razak, T., Garibaldi, J. M., Wagner, C., Pourabdollah, A., & Soria, D. (in press). Interpretability indices for hierarchical fuzzy systems. doi:10.1109/FUZZ-IEEE.2017.8015616
DOI https://doi.org/10.1109/FUZZ-IEEE.2017.8015616
Publisher URL http://ieeexplore.ieee.org/document/8015616/
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingh.../end_user_agreement.pdf
Additional Information Published in Proceedings of the IEEE International Fuzzy Systems Conference. IEEE, 2017. ISBN: 9781509060344. DOI: 10.1109/FUZZ-IEEE.2017.8015616

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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