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Shared domains of competence of approximate learning models using measures of separability of classes., and . Inf. Sci., 185 (1): 43-65 (2012)A Study on the Noise Label Influence in Boosting Algorithms: AdaBoost, GBM and XGBoost., , and . HAIS, volume 10334 of Lecture Notes in Computer Science, page 268-280. Springer, (2017)Transforming big data into smart data: An insight on the use of the k-nearest neighbors algorithm to obtain quality data., , , , , and . WIREs Data Mining Knowl. Discov., (2019)KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework., , , , and . J. Multiple Valued Log. Soft Comput., 17 (2-3): 255-287 (2011)Synthetic Sample Generation for Label Distribution Learning., , , and . Inf. Sci., (2021)Multiple instance classification: Bag noise filtering for negative instance noise cleaning., , , and . Inf. Sci., (2021)DILS: Constrained clustering through dual iterative local search., , , and . Comput. Oper. Res., (2020)On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification., , , , and . Neurocomputing, (2014)A robust approach for deep neural networks in presence of label noise: relabelling and filtering instances during training., , and . CoRR, (2021)Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness., , , and . Inf. Sci., (2013)