| Class imbalance methods for translation initiation site recognition in DNA sequences N García-Pedrajas, J Pérez-Rodríguez, M García-Pedrajas, D Ortiz-Boyer, ... Knowledge-Based Systems 25 (1), 22-34, 2012 | 102 | 2012 |
| OligoIS: Scalable instance selection for class-imbalanced data sets N García-Pedrajas, J Perez-Rodriguez, A de Haro-García IEEE Transactions on Cybernetics 43 (1), 332-346, 2012 | 66 | 2012 |
| A scalable approach to simultaneous evolutionary instance and feature selection NS GarcíA-Pedrajas, A De Haro-GarcíA, J PéRez-RodríGuez Information Sciences 228, 150-174, 2013 | 60 | 2013 |
| Simultaneous instance and feature selection and weighting using evolutionary Computation: Proposal and Study J Pérez-Rodríguez, AG Arroyo-Peña, N García-Pedrajas Applied Soft Computing 37, 416-443, 2015 | 55 | 2015 |
| A scalable memetic algorithm for simultaneous instance and feature selection N García-Pedrajas, A de Haro-García, J Pérez-Rodríguez Evolutionary Computation 22 (1), 1-45, 2014 | 39 | 2014 |
| Multi-selection of instances: A straightforward way to improve evolutionary instance selection N García-Pedrajas, J Pérez-Rodríguez Applied Soft Computing 12 (11), 3590-3602, 2012 | 28 | 2012 |
| A general framework for boosting feature subset selection algorithms J Pérez-Rodríguez, A de Haro-Garcia, JAR del Castillo, ... Information Fusion 44, 147-175, 2018 | 21 | 2018 |
| Combining three strategies for evolutionary instance selection for instance-based learning A de Haro-García, J Pérez-Rodríguez, N García-Pedrajas Swarm and Evolutionary Computation 42, 160-172, 2018 | 18 | 2018 |
| Regularized ensemble neural networks models in the extreme learning machine framework C Perales-González, M Carbonero-Ruz, D Becerra-Alonso, ... Neurocomputing 361, 196-211, 2019 | 10 | 2019 |
| An evolutionary algorithm for gene structure prediction J Pérez-Rodríguez, N García-Pedrajas International Conference on Industrial, Engineering and Other Applications …, 2011 | 10 | 2011 |
| Negative correlation learning in the extreme learning machine framework C Perales-González, M Carbonero-Ruz, J Perez-Rodriguez, ... Neural Computing and Applications 32, 13805-13823, 2020 | 9 | 2020 |
| Global negative correlation learning: A unified framework for global optimization of ensemble models C Perales-González, F Fernández-Navarro, M Carbonero-Ruz, ... IEEE Transactions on Neural Networks and Learning Systems 33 (8), 4031-4042, 2021 | 8 | 2021 |
| Negative correlation hidden layer for the extreme learning machine C Perales-González, F Fernández-Navarro, J Pérez-Rodríguez, ... Applied Soft Computing 109, 107482, 2021 | 5 | 2021 |
| Floating search methodology for combining classification models for site recognition in DNA sequences J Pérez-Rodríguez, A de Haro-García, N García-Pedrajas IEEE/ACM Transactions on Computational Biology and Bioinformatics 18 (6 …, 2020 | 4 | 2020 |
| Instance selection for class imbalanced problems by means of selecting instances more than once J Pérez-Rodríguez, A de Haro-García, N García-Pedrajas Conference of the Spanish Association for Artificial Intelligence, 104-113, 2011 | 4 | 2011 |
| Estimating ensemble weights for bagging regressors based on the mean–variance portfolio framework J Pérez-Rodríguez, F Fernández-Navarro, T Ashley Expert Systems with Applications 229, 120462, 2023 | 3 | 2023 |
| Machine Learning Algorithms and Applications in Engineering P Chatterjee, M Yazdani, F Fernández-Navarro, J Pérez-Rodríguez CRC Press, 2023 | 3 | 2023 |
| Evolutionary computation, combined with support vector machines, for gene structure prediction J Pérez-Rodríguez, N García-Pedrajas 2011 11th International Conference on Intelligent Systems Design and …, 2011 | 3 | 2011 |
| Boosting ridge for the extreme learning machine globally optimised for classification and regression problems C Peralez-González, J Pérez-Rodríguez, AM Durán-Rosal Scientific Reports 13 (1), 11809, 2023 | 2 | 2023 |
| Stepwise approach for combining many sources of evidence for site-recognition in genomic sequences J Pérez-Rodríguez, N García-Pedrajas BMC bioinformatics 17, 1-16, 2016 | 2 | 2016 |
