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Export results:
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Filters: Author is J. R. Cano  [Clear All Filters]
2018
A First Attempt on Monotonic Training Set Selection, Cano, J. R., and García S. , Hybrid Artificial Intelligent Systems, Cham, p.277–288, (2018)
Credal C4.5 with Refinement of Parameters, Mantas, Carlos J., Abellán Joaquín, Castellano Javier G., Cano J. R., and Moral Serafín , Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, Cham, p.739–747, (2018)
2016
A Nearest Hyperrectangle Monotonic Learning Method, García, Javier, Cano J. R., and García S. , Proceedings of the 11th International Conference Hybrid Artificial Intelligent Systems, 2016, Seville, Spain, April 18-20, 2016, p.311–322, (2016)
Hyperrectangles Selection for Monotonic Classification by Using Evolutionary Algorithms, García, Javier, Al-bar Adnan, Aljohani Naif R., Cano J. R., and García S. , International Journal Computational Intelligence Systems, Volume 9, Number 1, p.184–201, (2016)
2013
Analysis of data complexity measures for classification, Cano, J. R. , Expert Systems with Applications, Volume 40, Number 12, p.4820–4831, (2013)
2010
A Review on Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, p.92–113, (2010)
2009
Diagnose of Effective Evolutionary Prototype Selection using an Overlapping Measure, García, S., Cano J. R., Bernadó-Mansilla E., and Herrera F. , International Journal of Pattern Recognition and Artificial Intelligence, Volume 23, Number 8, p.1527-1548, (2009)
Modelo predictivo colaborativo de apoyo al diagnóstico en servicio de urgencias psiquiátricas, Cano, J. R., González P., Aguilera José, López-Herrera A.G., Herrera F., Navío M., and Angel Jiménez-Arriero Miguel , Revista Ibérica de Sistemas y Tecnologías de la información, Volume 4, Number 4, p.29-42, (2009)
2008
A memetic algorithm for Evolutionary Prototype Selection: A Scaling Up Approach, García, S., Cano J. R., and Herrera F. , Pattern Recognition, Volume 41, Number 8, p.2693-2709, (2008)
Estudio de la influencia de las medidas de complejidad de los datos en los Sistemas de Clasifcación Basados en Reglas Difusas: Análisis de la Razón Discriminante de Fisher, Luengo, J., García S., Cano J. R., and Herrera F. , XIV Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Mieres (Spain), p.257-263, (2008)
Evolutionary Stratified Instance Selection applied to Training Set Selection for Extracting High Precise-Interpretable Classification Rules, Cano, J. R., Herrera F., and Lozano Manuel , 01, (2008)
Making CN1 -SD Subgroup Discovery Algorithm Scalable to Large Size Data Sets Using Instance Selection, Cano, J. R., Herrera F., Lozano Manuel, and García Salvador , Expert System with Applications, Volume 35, Number 4, p.1949-1965, (2008)
Making CN2-SD Subgroup Discovery Algorithm scalable to Large Size Data Sets using Instance Selection, Cano, J. R., Herrera F., Lozano M., and García S. , Expert Systems with Applications, Volume 35, p.1949-1965, (2008)
Replacement strategies to preserve useful diversity in steady-state genetic algorithms, Lozano, M., Cano J. R., and Herrera F. , Information Sciences, Volume 178, Number 23, p.4421–4433, (2008)
Subgroup Discovery in Large Size Data Sets Preprocessed Using Stratified Instance Selection for Increasing the Presence of Minority Classes, Cano, J. R., García S., and Herrera F. , Pattern Recognition Letters, Volume 29, p.2156-2164, (2008)
2006
A proposal of Evolutionary Prototype Selection for Class Imbalance Problems, García, S., Cano J. R., Fernández A., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1415-1423, (2006)
Incorporating Knowledge in Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1358-1366, (2006)
On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Applied Soft Computing, Volume 6, p.323-332, (2006)
2005
A Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Soft Computing: Methodologies and Applications, p.271-284, (2005)
De la teoría a la práctica: una reflexión sobre el EEES en aula, Romero, Samuel, Cano J. R., Prados-Suarez María Belen, and Rivero-Cejudo Maria Linarejos , Adaptación del profesorado universitario al espacio europeo de educación superior mediante el uso de nuevas tecnologías, Number 69-77, Jaén (España), (2005)
Instance Selection Using Evolutionary Algorithms: An Experimental Study, Cano, J. R., Herrera F., and Lozano Manuel , Advanced Techniques in Knowledge Discovery and Data Mining, London, p.127–152, (2005)
Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms, Lozano, Manuel, Herrera F., and Cano J. R. , 01, p.85-96, (2005)
Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining, Cano, J. R., Herrera F., and Lozano Manuel , Evolutionary Computation in Data Mining, Berlin, Heidelberg, p.21–39, (2005)
Stratification for Scaling Up Evolutionary Prototype Selection, Cano, J. R., Herrera F., and Lozano M. , Pattern Recognition Letters, Volume 26, p.953-963, (2005)
Técnicas de reducción de datos en KDD, Cano, J. R., and Herrera F. , Minería de datos: Técnicas y Aplicaciones, Number 13-33, Sevilla (España), (2005)
2003
An Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
Linguistic Modeling with Hierarchical Systems of Weighted Linguistic Rules, Alcalá, R., Cano J. R., Cordón O., Herrera F., Villar P., and Zwir I. , International Journal of Approximate Reasoning, Volume 32, Number 2-3, p.187-215, (2003)
Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms, Lozano, M., Herrera F., and Cano J. R. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
Using Evolutionary Algorithms as Instance Selection for Data Reduction in KDD: an Experimental Study, Cano, J. R., Herrera F., and Lozano M. , IEEE Transactions on Evolutionary Computation, Volume 7, Number 6, p.561-575, (2003)
2002
A GRASP Algorithm for Clustering, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Proceedings of the 8th Ibero-American Conference on Artifical Intelligence, Seville, Spain, November 12-15, 2002,, p.214–223, (2002)
A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Journal of Intelligent and Fuzzy Systems, Volume 12, Number 3-4, p.235–242, (2002)
Scrae Web: Sistema de Corrección y Revisión Automática de Exámenes a Través de la Web, Pulido, Alfredo Sanchez, Cano J. R., and Pavón-Pulido Nieves , Jornadas de Enseñanza Universitaria de la Informática Jenui , 01, Cáceres (España), (2002)
Selección Evolutiva de Instancias en Minería de Datos, Cano, J. R., Herrera F., and Lozano Manuel , Workwhop de Minería de Datos y Aprendizaje Automático, 01, Santander (España), (2002)