From Decision Trees to Advanced Boosting: A Simple Yet Deep Guide to Tree-Based Models

Image created by the author using Figma If you’ve worked with tabular data, you’ve likely noticed something: No matter how advanced deep learning becomes, tree-based models often outperform everything else. From credit risk prediction to medical decision, models like XGBoost, LightGBM, and CatBoost dominate real-world machine learning tasks. But why are they so powerful? And how did we get from a simple decision tree to these highly optimized algorithms? This article breaks it down from first principles - in a way that builds intuition before diving into advanced concepts.