Imbalanced Classification in real world datasets
Classification is a very common use case in machine learning and is taught in many courses with somewhat balanced datasets, but many real-world use-cases have datasets with an imbalanced distribution of categories/classes to be classified. Standard approaches for balanced classification will give the illusion of good accuracy when accuracy itself becomes a misguiding metric for evaluation when data has...