Gacto, M. J., Galende, M., Alcalá, R., & Herrera Triguero, F. (2013). Obtaining accurate TSK Fuzzy Rule-Based Systems by Multi-Objective Evolutionary Learning in high-dimensional regression problems. 1-7. (Original work published 2013)
Francisco Herrera Triguero
First name
Francisco
Last name
Herrera Triguero
2013
2012
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2012). Aprendizaje Evolutivo De Sistemas Aproximativos De Tipo TSK Para Problemas De Alta Dimensionalidad. 295-300. Valladolid (Spain). (Original work published 2026)
López, V., Fernández, A., del Jesus Díaz, M. J., & Herrera Triguero, F. (2012). Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations. 2. (Original work published)
García López, S., Derrac, J., Triguero, I., Carmona, C. J., & Herrera Triguero, F. (2012). Evolutionary-Based Selection of Generalized Instances for Imbalanced Classification. Knowledge-Based Systems, 25, 3-12. https://doi.org/10.1016/j.knosys.2011.01.012
Villar, P., Fernández Hilario, A. L., Carrasco, R., & Herrera Triguero, F. (2012). Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classication Systems for Highly Imbalanced Data-Sets. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 20, 369-397. https://doi.org/10.1142/S0218488512500195
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2012). Improving Multi-label Classifiers via Label Reduction with Association Rules. 188-199. Salamanca (Spain). https://doi.org/10.1007/978-3-642-28931-6_18 (Original work published)
García López, S., Derrac, J., Cano De Amo, J. R., & Herrera Triguero, F. (2012). Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study. IEEE Transactions Pattern Analysis and Machiche Intelligence, 34, 417-435. https://doi.org/10.1109/TPAMI.2011.142
Lozano Márquez, M., Herrera Triguero, F., & Cano De Amo, J. R. (2012). Replacement Strategies to Preserve Useful Diversity in Steady-State Genetic Algorithms. Information Sciences.
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2012). A Multi-Objective Evolutionary Algorithm for an Effective Tuning of Fuzzy Logic Controllers in Heating, Ventilating and Air Conditioning Systems. Applied Intelligence, 36, 330-347. https://doi.org/10.1007/s10489-010-0264-x
López, V., Fernández, A., del Jesus Díaz, M. J., & Herrera Triguero, F. (2012). Un sistema de clasificación basado en reglas difusas jerárquico con programación genética para problemas de clasificación altamente no balanceados. Presentado en. (Original work published)