Tree Models and Ensembles#
Decision trees divide a feature space using learned thresholds. XGBoost builds an ensemble sequentially, with each new tree helping correct errors made by the existing collection of trees.
This framework-neutral notebook flattens the MNIST images and applies XGBoost directly. A short Example thought compares two maximum tree depths using validation error and runtime.