Probabilistic Decision-Making
Oversampling is a statistical technique used to increase the size of a dataset by duplicating instances from a minority class or by generating synthetic examples. This method is often employed in situations where the data is imbalanced, helping to improve the performance of models by ensuring that all classes are adequately represented in the sample, particularly when making decisions based on probabilistic models.
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