Dealing With Imbalanced Datasets

Summary: Dealing with imbalanced datasets is an everyday problem. SMOTE, Synthetic Minority Oversampling TEchnique and its variants are techniques for solving this problem through oversampling that have recently become a very popular way to improve model performance. There are some problems that never go away. Imbalanced datasets is one in which the majority case greatly outweighs the minority case. Years ago we dealt with this by naïve oversampling or, if we had enough data, even under sampling to get the dataset more in balance.