Oversampling and undersampling in data analysis
Oversampling and undersampling in data analysis are techniques used to adjust the class distribution of a data set (i.e. the ratio between the different classes/categories represented). Oversampling and undersampling are opposite and roughly equivalent techniques. They both involve using a bias to select more samples from one class than from another.