1. Target-Based Techniques (High Impact) These are extremely powerful for boosting model accuracy—especially with tree models like XGBoost, CatBoost, LightGBM. ✔ Target Encoding Replace categories with mean target values. Variants: K-fold TE, smoothing, leave-one-out Avoids overfitting while capturing signal ✔ Weight of Evidence (WoE) Used heavily in credit scorin... https://blogland.adseon.xyz/feature-engineering-tricks-used-by-top-data-scientists/