What is Synthetic Minority Over-Sampling Technique (SMOTE)?
Synthetic Minority Over-Sampling Technique, or SMOTE, is a statistical method used to address the problem of imbalanced datasets. This technique is particularly valuable in fields like epidemiology, where certain classes of data, such as rare diseases, may be significantly underrepresented. SMOTE works by generating synthetic samples for the minority class, thereby balancing the dataset and improving the performance of machine learning algorithms.
