Wieczynski, JonataLucca, GiancarloBorges, Eduardo N.Urío Larrea, AsierLópez Molina, CarlosBustince Sola, HumbertoPereira Dimuro, Graçaliz2024-12-102024-12-102024-09-27Wieczynski, J., Lucca, G., Borges, E., Urío-Larrea, A.,López Molina, C., Humberto, B., Dimuro, G. (2024) Application of the Sugeno integral in fuzzy rule-based classification. Applied Soft Computing, 167, 1-9. https://doi.org/10.1016/j.asoc.2024.112265.1568-494610.1016/j.asoc.2024.112265https://academica-e.unavarra.es/handle/2454/52677Fuzzy Rule-Based Classification System (FRBCS) is a well-known technique to deal with classification problems. Recent studies have considered the usage of the Choquet integral and its generalizations (e.g.: 𝐶𝑇 -integral, 𝐶𝐹 - Integral and 𝐶𝐶-integral) to enhance the performance of such systems. Such fuzzy integrals were applied to the Fuzzy Reasoning Method (FRM) to aggregate the fired fuzzy rules when classifying new data. However, the Sugeno integral, another well-known aggregation operator, obtained good results in other applications, such as brain–computer interfaces. These facts led to the present study, in which we consider the Sugeno integral in classification problems. That is, the Sugeno integral is applied in the FRM of a widely used FRBCS, and its performance is analyzed over 33 different datasets from the literature, also considering different fuzzy measures. To show the efficiency of this new approach, the results obtained are also compared with previous studies that involved the application of different aggregation functions. Finally, we perform a statistical analysis of the application.application/pdfeng© 2024 The Authors. This is an open access article under the CC BY license.Sugeno integralChoquet integralCT -integralCF -integralCC-integralFuzzy measuresFuzzy rule-based classification systeminfo:eu-repo/semantics/article2024-12-10info:eu-repo/semantics/openAccess