Fernández Hilario, A. L. . ., del Jesus Díaz, M. J. ., Cordón García, Óscar ., Marcelloni, F. ., & Herrera Triguero, F. . (2019). Evolutionary Fuzzy Sistems for Explainable Artificial Intelligence: Why, When, What for, and Where to ?. IEEE Computational Intelligence, 1, 69-81. https://doi.org/10.1109/TFUZZ.2018.2814577
Alberto Luis Fernández Hilario
First name
Alberto Luis
Last name
Fernández Hilario
2019
2018
Fernández Hilario, A. L. . ., Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. Proc. Of the XVIII Conferencia De La Asociación Española Para La Inteligencia Artificial (XVIII CAEPIA), 1316-1317.
2017
Fernández Hilario, A. L. . ., Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2017). A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. International Journal of Neural Systems, 27, 1-17. https://doi.org/10.1142/S0129065717500289
Triguero, I. ., Gonzalez, S. ., Moyano, J. ., García López, S. ., Alcala-Fdez, J. ., Luengo, J. ., … PRESS., A. . (2017). KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. International Journal of Computational Intelligence Systems, 10, 1238-1249.
2016
Fernández Hilario, A. L. . ., Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2016). A View on Fuzzy Systems for Big Data: Progress and Opportunities. International Journal of Computational Intelligence Systems, 9, 69-80.
2014
Rivera Rivas, A. J. ., Espinilla, M. ., Fernández Hilario, A. L. . ., López, J. S., & Charte Ojeda, F. . (2014). Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información. Enseñanza Y Aprendizaje De ingeniería De Computadores. Revista De Experiencias Docentes En ingeniería De Computadores, 4, 15-24.
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
Chávez, F. ., Fernández Hilario, A. L. . ., Gacto, M. J., & Alcalá, R. . (2012). Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems. International Journal of Computational Intelligence Systems, 5, 368-386. https://doi.org/10.1080/18756891.2012.685327
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