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.
Manuel Lozano Márquez
First name
Manuel
Last name
Lozano Márquez
2012
2008
Cano De Amo, J. R., Herrera Triguero, F., Lozano Márquez, M., & García López, S. (2008). Making CN2-SD Subgroup Discovery Algorithm scalable to Large Size Data Sets using Instance Selection. Expert Systems with Applications, 35, 1949-1965.
Lozano Márquez, M., Cano De Amo, J. R., & Herrera Triguero, F. (2008). Replacement strategies to preserve useful diversity in steady-state genetic algorithms. Information Sciences, 178, 4421-4433. https://doi.org/10.1016/j.ins.2008.07.031
2007
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2007). Evolutionary Stratified Training Set Selection for Extracting Classification Rules with trade off Precision-Interpretability. Data \& Knowledge Engineering, 60, 90-108.
2006
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2006). On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining. Applied Soft Computing, 6, 323-332.
2005
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2005). A Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining (F. Hoffmann, M. Köppen, F. Klawonn, & R. Roy, Eds.). Springer-Verlag.
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2005). Stratification for Scaling Up Evolutionary Prototype Selection. Pattern Recognition Letters, 26, 953-963.
2004
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2004). Selección Evolutiva Estratificada de Conjuntos de Entrenamiento para la Obtención de Bases de Reglas con un Alto Equilibrio entre Precisión e Interpretabilidad (R. Giráldez, J. C. Riquelme, & J. S. Aguilar, Eds.).
2003
Cano De Amo, J. R., Herrera Triguero, F., & Lozano Márquez, M. (2003). An Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining. Presentado en. (Original work published 2026)
Lozano Márquez, M., Herrera Triguero, F., & Cano De Amo, J. R. (2003). Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms. Presentado en. (Original work published 2026)