Why is Random Under Sampling Important in Epidemiology?
Epidemiological studies often deal with binary classification problems, such as predicting the presence or absence of a disease. In many cases, the number of instances of the disease (positive class) is significantly lower than the number of non-disease instances (negative class). This imbalance can lead to models that are biased towards the majority class, thus reducing the ability to correctly identify true cases of the disease.
