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A Survey on Data Augmentation for Text Classification
[article]
2022
arXiv
pre-print
Data augmentation, the artificial creation of training data for machine learning by transformations, is a widely studied research field across machine learning disciplines. While it is useful for increasing a model's generalization capabilities, it can also address many other challenges and problems, from overcoming a limited amount of training data, to regularizing the objective, to limiting the amount data used to protect privacy. Based on a precise description of the goals and applications
arXiv:2107.03158v4
fatcat:cjw5zo7p3rdfxiy5w5pvk7av2m