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
Galar, M. ., Fernández Hilario, A. L. . ., Barrenechea, E. ., Bustince, H. ., & Herrera Triguero, F. . (2012). A Review on Ensembles for Class Imbalance Problem: Bagging, Boosting and Hybrid Based Approaches. IEEE Transactions on System, Man and Cybernetics - Part C: Applications and Reviews, 42, 463-484. https://doi.org/10.1109/TSMCC.2011.2161285
López, V. ., Fernández Hilario, A. L. . ., Moreno-Torres, J. ., & Herrera Triguero, F. . (2012). Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics. Expert Systems With Applications, 39, 6585-6608. https://doi.org/10.1016/j.eswa.2011.12.043
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 2025)
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.