Fernández Hilario, A. L., del Jesus Díaz, M. J., Cordón García, Ó., 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