Data augmentation
Data analysis technique / From Wikipedia, the free encyclopedia
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Data augmentation is a statistical technique which allows maximum likelihood estimation from incomplete data.[1][2] Data augmentation has important applications in Bayesian analysis,[3] and the technique is widely used in machine learning to reduce overfitting when training machine learning models,[4] achieved by training models on several slightly-modified copies of existing data.
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