Oversampling

Oversampling is a technique used in data processing, particularly in the context of imbalanced datasets, where one class (or category) is significantly overrepresented compared to others. This imbalance can negatively affect the performance of machine learning models, as they may become biased towards the majority class and fail to learn the characteristics of the minority class effectively. In oversampling, instances of the minority class are artificially increased to balance the ratio between the minority and majority classes.