| Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study I Triguero, S García, F Herrera Knowledge and Information Systems 42, 245-284, 2015 | 690 | 2015 |
| kNN-IS: An Iterative Spark-based design of the k-Nearest Neighbors classifier for big data J Maillo, S Ramírez, I Triguero, F Herrera Knowledge-Based Systems 117, 3-15, 2017 | 386 | 2017 |
| Multi-head CNN–RNN for multi-time series anomaly detection: An industrial case study M Canizo, I Triguero, A Conde, E Onieva Neurocomputing 363, 246-260, 2019 | 374 | 2019 |
| A taxonomy and experimental study on prototype generation for nearest neighbor classification I Triguero, J Derrac, S Garcia, F Herrera IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2011 | 338 | 2011 |
| KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García, J Alcalá-Fdez, J Luengo, ... International Journal of Computational Intelligence Systems 10 (1), 1238-1249, 2017 | 290 | 2017 |
| MRPR: A MapReduce solution for prototype reduction in big data classification I Triguero, D Peralta, J Bacardit, S García, F Herrera neurocomputing 150, 331-345, 2015 | 281 | 2015 |
| Transforming big data into smart data: An insight on the use of the k‐nearest neighbors algorithm to obtain quality data I Triguero, D García‐Gil, J Maillo, J Luengo, S García, F Herrera Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9 (2 …, 2019 | 244 | 2019 |
| A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation D Peralta, M Galar, I Triguero, D Paternain, S García, E Barrenechea, ... Information Sciences 315, 67-87, 2015 | 202 | 2015 |
| ROSEFW-RF: the winner algorithm for the ECBDL’14 big data competition: an extremely imbalanced big data bioinformatics problem I Triguero, S Del Río, V López, J Bacardit, JM Benítez, F Herrera Knowledge-Based Systems 87, 69-79, 2015 | 190 | 2015 |
| Evolutionary feature selection for big data classification: A mapreduce approach D Peralta, S Del Río, S Ramírez-Gallego, I Triguero, JM Benitez, ... Mathematical Problems in Engineering 2015 (1), 246139, 2015 | 180 | 2015 |
| Evolutionary-based selection of generalized instances for imbalanced classification S Garcı, I Triguero, CJ Carmona, F Herrera Knowledge-Based Systems 25 (1), 3-12, 2012 | 171 | 2012 |
| Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification I Triguero, S García, F Herrera Pattern recognition 44 (4), 901-916, 2011 | 155 | 2011 |
| On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification I Triguero, JA Sáez, J Luengo, S García, F Herrera Neurocomputing 132, 30-41, 2014 | 111 | 2014 |
| On the use of convolutional neural networks for robust classification of multiple fingerprint captures D Peralta, I Triguero, S García, Y Saeys, JM Benitez, F Herrera International Journal of Intelligent Systems 33 (1), 213-230, 2018 | 109 | 2018 |
| A mapreduce-based k-nearest neighbor approach for big data classification J Maillo, I Triguero, F Herrera 2015 IEEE Trustcom/BigDataSE/ISPA 2, 167-172, 2015 | 106 | 2015 |
| A review on the self and dual interactions between machine learning and optimisation H Song, I Triguero, E Özcan Progress in Artificial Intelligence 8 (2), 143-165, 2019 | 100 | 2019 |
| A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models M Galar, J Derrac, D Peralta, I Triguero, D Paternain, C Lopez-Molina, ... Knowledge-based systems 81, 76-97, 2015 | 97 | 2015 |
| Fast fingerprint identification for large databases D Peralta, I Triguero, R Sanchez-Reillo, F Herrera, JM Benítez Pattern Recognition 47 (2), 588-602, 2014 | 91 | 2014 |
| SEG-SSC: A Framework Based on Synthetic Examples Generation for Self-Labeled Semi-Supervised Classification I Triguero, S García IEEE Transactions on Cybernetics 45 (4), 622-634, 2015 | 83 | 2015 |
| Evolutionary undersampling for extremely imbalanced big data classification under apache spark I Triguero, M Galar, D Merino, J Maillo, H Bustince, F Herrera 2016 IEEE congress on evolutionary computation (CEC), 640-647, 2016 | 81 | 2016 |
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, Spaindecsai.ugr.es의 이메일 확인됨