Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-sets Using an Evolutionary Adaptive Inference System. 5517, 294-301. Salamanca (Spain). (Original work published 2026)
Francisco Herrera Triguero
First name
Francisco
Last name
Herrera Triguero
2009
Luengo, J., Fernández Hilario, A. L., Herrera Triguero, F., & García López, S. (2009). Addressing Data-Complexity for Imbalanced Data-sets: A Preliminary Study on the Use of Preprocessing for C4.5. 523-528.
Alcala-Fdez, J., Sánchez, L., García López, S., del Jesus Díaz, M. J., Ventura, S., Garrell, J., … Herrera Triguero, F. (2009). KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems. Soft Computing, 13, 307-318. https://doi.org/10.1007/s00500-008-0323-y
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2009). Algoritmo Genético Multi-Objetivo Avanzado para el ajuste de un sistema difuso aplicado al Control de Sistemas de Ventilación, Calefacción y Aire Acondicionado. 595-602. (Original work published 2026)
Alcala-Fdez, J., Alcalá, R., Gacto, M. J., & Herrera Triguero, F. (2009). Learning the Membership Function Contexts for Mining Fuzzy Association Rules by Using Genetic Algorithms. Fuzzy Sets and Systems, 160, 905-921. https://doi.org/10.1016/j.fss.2008.05.012
Carmona, C. J., González García, P., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery. 1706-1711. ICC Jeju, Jeju Island, Korea. (Original work published 2026)
Cano De Amo, J. R., González García, P., García, J. J. A., López-Herrera, A., Herrera Triguero, F., Navío, M., & Angel, J.-A. M. (2009). Modelo predictivo colaborativo de apoyo al diagnóstico en servicio de urgencias psiquiátricas. Revista Ibérica de Sistemas y Tecnologías de la información, 4, 29-42.
García López, S., Cano De Amo, J. R., Bernadó-Mansilla, E., & Herrera Triguero, F. (2009). Diagnose of Effective Evolutionary Prototype Selection using an Overlapping Measure. International Journal of Pattern Recognition and Artificial Intelligence, 23, 1527-1548.
Carmona, C. J., González García, P., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup Discovery. 5572, 573-580. Salamanca (Spain): Springer. (Original work published 2026)
García López, S., Fernández Hilario, A. L., & Herrera Triguero, F. (2009). Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems. Applied Soft Computing, 9, 1304-1314. https://doi.org/10.1016/j.asoc.2009.04.004