| Prototype selection for nearest neighbor classification: Taxonomy and empirical study S Garcia, J Derrac, J Cano, F Herrera IEEE transactions on pattern analysis and machine intelligence 34 (3), 417-435, 2012 | 748 | 2012 |
| Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study JR Cano, F Herrera, M Lozano IEEE transactions on evolutionary computation 7 (6), 561-575, 2003 | 432 | 2003 |
| A memetic algorithm for evolutionary prototype selection: A scaling up approach S García, JR Cano, F Herrera Pattern Recognition 41 (8), 2693-2709, 2008 | 225 | 2008 |
| Replacement strategies to preserve useful diversity in steady-state genetic algorithms M Lozano, F Herrera, JR Cano Information sciences 178 (23), 4421-4433, 2008 | 217 | 2008 |
| Stratification for scaling up evolutionary prototype selection JR Cano, F Herrera, M Lozano Pattern Recognition Letters 26 (7), 953-963, 2005 | 151 | 2005 |
| Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability JR Cano, F Herrera, M Lozano Data & Knowledge Engineering 60 (1), 90-108, 2007 | 121 | 2007 |
| On the combination of evolutionary algorithms and stratified strategies for training set selection in data mining JR Cano, F Herrera, M Lozano Applied Soft Computing 6 (3), 323-332, 2006 | 105 | 2006 |
| Analysis of data complexity measures for classification JR Cano Expert systems with applications 40 (12), 4820-4831, 2013 | 66 | 2013 |
| Monotonic classification: An overview on algorithms, performance measures and data sets JR Cano, PA Gutiérrez, B Krawczyk, M Woźniak, S García Neurocomputing 341, 168-182, 2019 | 65 | 2019 |
| Linguistic modeling with hierarchical systems of weighted linguistic rules R Alcalá, JR Cano, O Cordón, F Herrera, P Villar, I Zwir International Journal of Approximate Reasoning 32 (2-3), 187-215, 2003 | 35 | 2003 |
| Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes JR Cano, S García, F Herrera Pattern Recognition Letters 29 (16), 2156-2164, 2008 | 33 | 2008 |
| A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure JR Cano, O Cordón, F Herrera, L Sánchez Journal of Intelligent & Fuzzy Systems 12 (3-4), 235-242, 2002 | 30 | 2002 |
| CommuniMents: A framework for detecting community based sentiments for events MA Jarwar, RA Abbasi, M Mushtaq, O Maqbool, NR Aljohani, A Daud, ... International Journal on Semantic Web and Information Systems (IJSWIS) 13 (2 …, 2017 | 29 | 2017 |
| Diagnose effective evolutionary prototype selection using an overlapping measure S García, JR Cano, E Bernado-Mansilla, F Herrera International Journal of Pattern Recognition and Artificial Intelligence 23 …, 2009 | 26 | 2009 |
| A proposal of evolutionary prototype selection for class imbalance problems S García, JR Cano, A Fernández, F Herrera Intelligent Data Engineering and Automated Learning–IDEAL 2006: 7th …, 2006 | 24 | 2006 |
| A GRASP algorithm for clustering JR Cano, O Cordón, F Herrera, L Sánchez IBERAMIA, 214-223, 2002 | 23 | 2002 |
| Prototype selection to improve monotonic nearest neighbor JR Cano, NR Aljohani, RA Abbasi, JS Alowidbi, S Garcia Engineering Applications of Artificial Intelligence 60, 128-135, 2017 | 22 | 2017 |
| Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection JR Cano, F Herrera, M Lozano, S García Expert Systems with Applications 35 (4), 1949-1965, 2008 | 22 | 2008 |
| Replacement strategies to maintain useful diversity in steady-state genetic algorithms M Lozano, F Herrera, JR Cano Soft Computing: Methodologies and Applications, 85-96, 2005 | 20 | 2005 |
| Hyperrectangles selection for monotonic classification by using evolutionary algorithms J García, AM AlBar, NR Aljohani, JR Cano, S García International Journal of Computational Intelligence Systems 9 (1), 184-201, 2016 | 17 | 2016 |
