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
Alberto Luis Fernández Hilario
First name
Alberto Luis
Last name
Fernández Hilario
2012
2011
Sanz, J., Fernández Hilario, A. L., Bustince, H., & Herrera Triguero, F. (2011). A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position. International Journal of Approximate Reasoning, 52, 751-766. https://doi.org/10.1016/j.ijar.2011.0
Luengo, J., Fernández Hilario, A. L., García López, S., & Herrera Triguero, F. (2011). Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling. Soft Computing, 15, 1909-1936. https://doi.org/10.1007/s00500-010-0625-8
Alcala-Fdez, J., Fernández Hilario, A. L., Luengo, J., Derrac, J., García López, S., Sánchez, L., & Herrera Triguero, F. (2011). KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework. Journal of Multiple-Valued Logic and Soft Computing, 17, 255-287.
2010
García López, S., Fernández Hilario, A. L., Luengo, J., & Herrera Triguero, F. (2010). Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power. Information Sciences, 180, 2044-2064. https://doi.org/10.1016/j.ins.2009.12.010
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2010). Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection. 69-74. Mieres (Spain). (Original work published 2026)
Fernández Hilario, A. L., Luengo, J., García López, S., Bernadó-Mansilla, E., & Herrera Triguero, F. (2010). Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation, 14, 913-941. https://doi.org/10.1109/TEVC.2009.2039140
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2010). On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets. Information Sciences, 180, 1268-1291. https://doi.org/10.1016/j.ins.2009.12.014
Sanz, J., Fernández Hilario, A. L., Bustince, H., & Herrera Triguero, F. (2010). Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning. Information Sciences, 180, 3674-3685. https://doi.org/10.1016/j.ins.2010.06.018
Fernández Hilario, A. L., Calderón, M., Barrenechea, E., Bustince, H., & Herrera Triguero, F. (2010). Solving Multi-Class Problems with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning and Preference Relations. Fuzzy Sets and Systems, 161, 3064-3080. https://doi.org/10.1016/j.fss.2010.05.016