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 | 186 | 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 | 70 | 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 (4), 367-388, 2015 | 36 | 2015 |
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 | 34 | 2017 |
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 | 32 | 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 | 27 | 2018 |
Chain based sampling for monotonic imbalanced classification S González, S García, ST Li, F Herrera Information Sciences 474, 187-204, 2019 | 21 | 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 | 9 | 2020 |
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 | 7 | 2016 |
Managing monotonicity in classification by a pruned adaboost S González, F Herrera, S García International Conference on Hybrid Artificial Intelligence Systems, 512-523, 2016 | 5 | 2016 |
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 | 4 | 2021 |
Managing monotonicity in classification by a pruned random forest S González, F Herrera, S García International Conference on Intelligent Data Engineering and Automated …, 2015 | 2 | 2015 |
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 |