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.
Francisco Herrera Triguero
First name
Francisco
Last name
Herrera Triguero
2009
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
Fernández Hilario, A. L., Herrera Triguero, F., & del Jesus Díaz, M. J. (2009). On the influence of an adaptive inference system in fuzzy rule-based classification sytems for imbalanced data-sets. Expert Systems With Applications, 36, 9805-9812. https://doi.org/10.1016/j.eswa.2009.02.048
Romero, C., González García, P., Ventura, S., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data. Expert Systems With Applications, 36, 1632-1644.
García López, S., Fernández Hilario, A. L., & Herrera Triguero, F. (2009). Un Primer Estudio sobre la Utilización de Selección Evolutiva de Conjuntos de Entrenamiento en Problemas de Clasificación con Clases no Balanceadas y árboles de Decisión. 183-190. Málaga (Spain). (Original work published 2026)
Fernández Hilario, A. L., Berlanga, F., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets. 42-47. Lisbon (Portugal).
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2009). Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm. 109-114. Pisa (Italy). (Original work published 2026)
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2009). A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability. 1146-1151. Lisbon, Portugal: IFSA/EUSFLAT 2009. (Original work published 2026)
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Hierarchical fuzzy rule based classfication systems with genetic rule selection for imbalanced data-sets. International Journal of Approximate Reasoning, 50, 561-577. https://doi.org/10.1016/j.ijar.2008.11.004