| Multilabel classification F Herrera, F Charte, AJ Rivera, MJ Del Jesus, F Herrera, F Charte, ... Multilabel Classification: Problem Analysis, Metrics and Techniques, 17-31, 2016 | 411 | 2016 |
| Addressing imbalance in multilabel classification: Measures and random resampling algorithms F Charte, AJ Rivera, MJ Del Jesus, F Herrera Neurocomputing 163, 3-16, 2015 | 316 | 2015 |
| MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation F Charte, AJ Rivera, MJ Del Jesus, F Herrera Knowledge-Based Systems 89, 385-397, 2015 | 283 | 2015 |
| A methodology for applying k-nearest neighbor to time series forecasting F Martínez, MP Frías, MD Pérez, AJ Rivera Artificial Intelligence Review 52 (3), 2019-2037, 2019 | 181 | 2019 |
| GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems FJ Berlanga, AJ Rivera, MJ del Jesús, F Herrera Information Sciences 180 (8), 1183-1200, 2010 | 158 | 2010 |
| A first approach to deal with imbalance in multi-label datasets F Charte, A Rivera, MJ del Jesus, F Herrera Hybrid Artificial Intelligent Systems: 8th International Conference, HAIS …, 2013 | 120 | 2013 |
| Dealing with seasonality by narrowing the training set in time series forecasting with kNN F Martínez, MP Frías, MD Pérez-Godoy, AJ Rivera Expert systems with applications 103, 38-48, 2018 | 98 | 2018 |
| Dealing with difficult minority labels in imbalanced mutilabel data sets F Charte, AJ Rivera, MJ del Jesus, F Herrera Neurocomputing 326, 39-53, 2019 | 69 | 2019 |
| MLeNN: a first approach to heuristic multilabel undersampling F Charte, AJ Rivera, MJ del Jesus, F Herrera Intelligent Data Engineering and Automated Learning–IDEAL 2014: 15th …, 2014 | 67 | 2014 |
| Concurrence among imbalanced labels and its influence on multilabel resampling algorithms F Charte, A Rivera, MJ del Jesus, F Herrera Hybrid Artificial Intelligence Systems: 9th International Conference, HAIS …, 2014 | 61 | 2014 |
| Time Series Forecasting with KNN in R: the tsfknn Package F Martínez, MP Frías, F Charte, AJ Rivera | 54 | 2019 |
| MEFASD-BD: multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments-a mapreduce solution F Pulgar-Rubio, AJ Rivera-Rivas, MD Pérez-Godoy, P González, ... Knowledge-Based Systems 117, 70-78, 2017 | 52 | 2017 |
| REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization F Charte, AJ Rivera, MJ del Jesus, F Herrera Neurocomputing 326, 110-122, 2019 | 49 | 2019 |
| Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines FJ Pulgar, F Charte, AJ Rivera, MJ del Jesus Information Fusion 54, 44-60, 2020 | 44 | 2020 |
| Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets MD Pérez-Godoy, A Fernández, AJ Rivera, MJ del Jesus Pattern Recognition Letters 31 (15), 2375-2388, 2010 | 44 | 2010 |
| LI-MLC: A label inference methodology for addressing high dimensionality in the label space for multilabel classification F Charte, AJ Rivera, MJ del Jesus, F Herrera IEEE transactions on neural networks and learning systems 25 (10), 1842-1854, 2014 | 42 | 2014 |
| Training algorithms for radial basis function networks to tackle learning processes with imbalanced data-sets MD Pérez-Godoy, AJ Rivera, CJ Carmona, MJ del Jesus Applied Soft Computing 25, 26-39, 2014 | 40 | 2014 |
| QUINTA: A question tagging assistant to improve the answering ratio in electronic forums F Charte, AJ Rivera, MJ del Jesus, F Herrera Ieee eurocon 2015-international conference on computer as a tool (eurocon), 1-6, 2015 | 39 | 2015 |
| A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks AJ Rivera, I Rojas, J Ortega, MJ del Jesus Soft Computing 11, 655-668, 2007 | 39 | 2007 |
| On the impact of imbalanced data in convolutional neural networks performance FJ Pulgar, AJ Rivera, F Charte, MJ del Jesus Hybrid Artificial Intelligent Systems: 12th International Conference, HAIS …, 2017 | 37 | 2017 |
María José Del Jesus DíazAssociate professor of Computer Science, University of JaénDirección de correo verificada de ujaen.es
