Handling Imbalanced Datasets in Classification Problems
Imbalanced datasets are one of the most common yet underestimated challenges in machine learning. Whether you're detecting fraud, diagnosing rare diseases, or flagging network intrusions, the reality is the same. The class you care about most is often the one you see the least. A model trained naively on such data can appear highly accurate while being practically useless, since it may simply...
