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Advances in domain adaptation for computer vision., , , and . Image Vis. Comput., (2021)An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics., , , , and . Inf. Sci., (2013)Enabling Smart Data: Noise filtering in Big Data classification., , , and . CoRR, (2017)Speech emotion recognition via multiple fusion under spatial-temporal parallel network., , , , , and . Neurocomputing, (October 2023)SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary., , , and . J. Artif. Intell. Res., (2018)OCAPIS: R package for Ordinal Classification and Preprocessing in Scala., , , and . Prog. Artif. Intell., 8 (3): 287-292 (2019)Special issue on Hybrid Fuzzy Models., , , and . Int. J. Hybrid Intell. Syst., 7 (1): 1 (2010)A First Attempt on Monotonic Training Set Selection., and . HAIS, volume 10870 of Lecture Notes in Computer Science, page 277-288. Springer, (2018)On the Use of Random Discretization and Dimensionality Reduction in Ensembles for Big Data., , , and . HAIS, volume 10870 of Lecture Notes in Computer Science, page 15-26. Springer, (2018)An empirical study on the joint impact of feature selection and data resampling on imbalance classification., , , , , , and . Appl. Intell., 53 (5): 5449-5461 (March 2023)