How Do You Handle Imbalanced Datasets in Machine Learning?
In machine learning, datasets often contain imbalances, where one class significantly outnumbers the others. For example, in fraud detection, fraudulent transactions form only a small percentage of the overall dataset. Handling such imbalances is crucial because models trained on unbalanced datasets tend to favor the majority class, leading to poor performance in predicting minority classes. […]