"LightGBM is a fast, efficient gradient boosting framework. In this article I show you how to visualize its decision trees using tools like plot_tree for basic plots, dtreeviz for enhanced visuals, graphviz for detailed rendering, and SuperTree for interactive exploration of complex tree structures."
"A Random Forest is a supervised machine learning algorithm used for classification and regression. This article demonstrates four ways to visualize Random Forests in Python, including feature importance plots, individual tree visualization using plot_tree, and SuperTree."
"XGBoost is a supervised machine learning algorithm used for both classification and regression tasks. This article demonstrates four ways to visualize XGBoost models in Python, including feature importance plots, individual tree visualization using plot_tree, dtreeviz, graphviz, and SuperTree."
