Imbalanced classes put “accuracy” out of business. This is a surprisingly common problem in machine learning (specifically in classification), occurring in datasets with a disproportionate ratio of observations in each class. Standard accuracy no longer reliably measures performance, which makes model training much trickier. Imbalanced classes appear in many domains, including: Fraud detection Spam filtering Disease screening SaaS subscription churn Advertising click-throughs In this … Continue reading How to Handle Imbalanced Classes in Machine Learning