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Fuzzy Rough Set Prototype Selection for Regression., , , , and . FUZZ-IEEE, page 1-8. IEEE, (2015)Fuzzy rough sets for self-labelling: An exploratory analysis., , , and . FUZZ-IEEE, page 931-938. IEEE, (2016)Multiple Instance Learning - Foundations and Algorithms, , , , , , and . Springer, (2016)Evolutionary undersampling for imbalanced big data classification., , , , , , and . CEC, page 715-722. IEEE, (2015)EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data., , , and . Neurocomputing, (2016)Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach., , , , and . Knowl. Inf. Syst., 56 (1): 55-84 (2018)IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification., , , , , , and . IEEE Trans. Fuzzy Syst., 23 (5): 1622-1637 (2015)Distributed fuzzy rough prototype selection for Big Data regression., , , , , , and . NAFIPS/WConSC, page 1-6. IEEE, (2015)Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods. Studies in Computational Intelligence Springer, (2019)Applications of Fuzzy Rough Set Theory in Machine Learning: a Survey., , , and . Fundam. Informaticae, 142 (1-4): 53-86 (2015)