Gacto, M. J., Alcalá, R. ., & Herrera Triguero, F. . (2011). A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based Systems (A. M. Fanelli, W. . Pedrycz, & A. . Petrosino, Eds.). Berlin, Heidelberg: Springer Berlin Heidelberg.
Francisco Herrera Triguero
First name
Francisco
Last name
Herrera Triguero
2011
Alcalá, R. ., Gacto, M. J., & Herrera Triguero, F. . (2011). A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems. IEEE Transactions on Fuzzy Systems, 19, 666-681. https://doi.org/10.1109/TFUZZ.2011.2131657
Sanz, J. ., Fernández Hilario, A. L. . ., Bustince, H. ., & Herrera Triguero, F. . (2011). A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position. International Journal of Approximate Reasoning, 52, 751-766. https://doi.org/10.1016/j.ijar.2011.0
Luengo, J. ., Fernández Hilario, A. L. . ., García López, S. ., & Herrera Triguero, F. . (2011). Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling. Soft Computing, 15, 1909-1936. https://doi.org/10.1007/s00500-010-0625-8
2010
Fernández Hilario, A. L. . ., Luengo, J. ., García López, S. ., Bernadó-Mansilla, E. ., & Herrera Triguero, F. . (2010). Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation, 14, 913-941. https://doi.org/10.1109/TEVC.2009.2039140
Berlanga, F. ., Rivera Rivas, A. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2010). GP-COACH: Genetic Programming-based learning of Compact and ACcurate fuzzy rule-based classification systems for High-dimensional problems. Information Sciences, 180, 1183-1200. https://doi.org/10.1016/j.ins.2009.12.020
Sanz, J. ., Fernández Hilario, A. L. . ., Bustince, H. ., & Herrera Triguero, F. . (2010). Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning. Information Sciences, 180, 3674-3685. https://doi.org/10.1016/j.ins.2010.06.018
Gacto, M. J., Alcalá, R. ., & Herrera Triguero, F. . (2010). Indice de Interpretabilidad Semántica para el Ajuste de Sistemas Basados en Reglas Difusas y Selección de Reglas Mediante un Algoritmo Evolutivo Multi-Objetivo. 73-78. Huelva. (Original work published 2025)
Gacto, M. J., Alcalá, R. ., & Herrera Triguero, F. . (2010). Integration of an Index to Preserve the Semantic Interpretability in the Multi-Objective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems. IEEE Transactions on Fuzzy Systems, 18, 515-531. https://doi.org/10.1109/TFUZZ.2010.2041008
Carmona, C. J. ., González García, P. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2010). NMEEF-SD: Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discovery. IEEE Transactions on Fuzzy Systems, 18, 958-970. https://doi.org/10.1109/TFUZZ.2010.2060200