Handling imbalanced classes, up-sampling, down-sampling, performance metric, penalize algorithm, tree-based algorithm, SMOTE algorithm
mbalanced 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: Free: Data Science Career Guide Learn how to land a high-paying job in data science and future-proof your career with the most efficient roadmap to learning DS & ML for busy professionals. Send My Download Fraud detection Spam filtering Disease screening SaaS subscription churn Advertising click-throughs In this guide, we’ll explore 5 effective ways to handle imbalanced classes. Intuition: Disease Screening Example Let’s say your client is a leading research hospital, and they’ve asked you to train a model f