| KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, ... Atlantis Press, 2017 | 254 | 2017 |
| A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities S González, S García, J Del Ser, L Rokach, F Herrera Information Fusion 64, 205-237, 2020 | 238 | 2020 |
| Monotonic random forest with an ensemble pruning mechanism based on the degree of monotonicity S González, F Herrera, S García New Generation Computing 33, 367-388, 2015 | 46 | 2015 |
| Evolutionary fuzzy rule-based methods for monotonic classification J Alcalá-Fdez, R Alcalá, S González, Y Nojima, S García IEEE Transactions on Fuzzy Systems 25 (6), 1376-1390, 2017 | 45 | 2017 |
| Class switching according to nearest enemy distance for learning from highly imbalanced data-sets S Gónzalez, S García, M Lázaro, AR Figueiras-Vidal, F Herrera Pattern Recognition 70, 12-24, 2017 | 42 | 2017 |
| DRCW-ASEG: One-versus-one distance-based relative competence weighting with adaptive synthetic example generation for multi-class imbalanced datasets ZL Zhang, XG Luo, S González, S García, F Herrera Neurocomputing 285, 176-187, 2018 | 36 | 2018 |
| Chain based sampling for monotonic imbalanced classification S González, S García, ST Li, F Herrera Information Sciences 474, 187-204, 2019 | 26 | 2019 |
| Preprocessing methodology for time series: An industrial world application case study JA Cortés-Ibáñez, S González, JJ Valle-Alonso, J Luengo, S García, ... Information sciences 514, 385-401, 2020 | 22 | 2020 |
| Fuzzy k-nearest neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise S González, S García, ST Li, R John, F Herrera Neurocomputing 439, 106-121, 2021 | 11 | 2021 |
| Comparison of KEEL versus open source Data Mining tools: Knime and Weka software J Alcala-Fdez, S Garcia, A Fernandez, J Luengo, S Gonzalez, JA Saez, ... Academic Press, 2016 | 8 | 2016 |
| Managing monotonicity in classification by a pruned adaboost S González, F Herrera, S García Hybrid Artificial Intelligent Systems: 11th International Conference, HAIS …, 2016 | 6 | 2016 |
| A benchmark for machine-learning based non-invasive blood pressure estimation using photoplethysmogram S González, WT Hsieh, TPC Chen Scientific Data 10 (1), 149, 2023 | 4 | 2023 |
| Managing monotonicity in classification by a pruned random forest S González, F Herrera, S García Intelligent Data Engineering and Automated Learning–IDEAL 2015: 16th …, 2015 | 2 | 2015 |
| Streamlined Framework for Agile Forecasting Model Development towards Efficient Inventory Management JH Soeseno, S González, TPC Chen arXiv preprint arXiv:2304.06344, 2023 | | 2023 |
| Interpretable estimation of the risk of heart failure hospitalization from a 30-second electrocardiogram S González, WT Hsieh, D Burba, TPC Chen, CL Wang, VCC Wu, ... 2022 E-Health and Bioengineering Conference (EHB), 1-4, 2022 | | 2022 |
| Preprocessing and ensemble approaches for singular problems: Monotonic and imbalanced classification S González Vázquez Universidad de Granada, 2020 | | 2020 |
| k-Vecinos más Cercanos Difuso para Clasificación Monotónica S González, S García, ST Li, R John, F Herrera XVIII Conferencia de la Asociación Española para la Inteligencia Artificial …, 2018 | | 2018 |
| Intercambio de Clases de acuerdo a la Distancia al Enemigo más Cercano para Problemas con Clases altamente No Balanceadas S González, M Lázaro, AR Figueiras-Vidal, S Garcıa, F Herrera XVII Conferencia de la Asociación Española para la Inteligencia Artificial …, 2016 | | 2016 |
| Clasificación Monotónica mediante poda de Bosques Aleatorios S González, F Herrera, S Garcıa CAEPIA'15 (Albacete), 2015 | | 2015 |
Francisco HerreraProfessor Computer Science and AI, Granada University, SpainVerified email at decsai.ugr.es
