Techniques for Handling Categorical Variables in Tree-Based Models
Introduction In the ever-evolving field of machine learning, tree-based models like Decision Trees, Random Forests, and Gradient Boosting Machines are powerful tools for both classification and regression tasks. These models are known for their interpretability, robustness to missing values, and ability to model non-linear relationships. However, data practitioners face one persistent challenge: handling categorical […]
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