Costa, Lucas Tubino BonifacioLucca, GiancarloPereira Dimuro, GraçalizBorges, Eduardo N.Emmendorfer, Leonardo R.Weigert, Stefan Cruz2022-02-012022-08-052021L. T. Bonifácio, G. Lucca, G. P. Dimuro, E. N. Borges, L. R. Emmendorfer and S. C. Weigert, 'Explainable Classification Methods for Fish Species Detection Using Hydroacoustic Data,' 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2021, pp. 1-6, doi: 10.1109/FUZZ45933.2021.9494446.97816654440711098-758410.1109/FUZZ45933.2021.9494446https://academica-e.unavarra.es/handle/2454/42091This work aims to evaluate explainable classification methods for the detection of fish species from hydroacoustic data acquired by echo sounders at a region near the coastline of south and southeastern Brazil. Decision trees and fuzzy rule-based methods were adopted. The fitted models were evaluated by quality measures based on the performance of the classifiers and also by an expert which analyzed the usefulness of the rules on describing the schools. The models learned by the algorithms performed well for the available data and were able to represent the documented behavior of the species considered in the studied region, according to the literature.7 p.application/pdfeng© 2021 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 workExplanabilityFish classificationFuzzy rule-based classification systemsHydroacousticsinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/openAccess