Interpretability indices for hierarchical fuzzy systems

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A. and Soria, D. 2017. Interpretability indices for hierarchical fuzzy systems. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017). Naples, Italy 09 - 12 Jul 2017 IEEE . doi:10.1109/FUZZ-IEEE.2017.8015616

TitleInterpretability indices for hierarchical fuzzy systems
AuthorsRazak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A. and Soria, D.
TypeConference paper
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.

Year2017
ConferenceIEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017)
PublisherIEEE
Accepted author manuscriptInterpretability Indices of HFSs - Final Version.pdf
Publication dates
Published24 Aug 2017
ISSN1558-4739
Digital Object Identifier (DOI)doi:10.1109/FUZZ-IEEE.2017.8015616

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