A fast gradient boosting model built from many decision trees.
XGBoost is like a team of picky test graders. Each grader hunts the mistakes the last one missed.
It predicts from table data, like loan risk or sales forecasts. It fixes errors round by round, but too many rounds can make it memorize the homework.
Gradient Boosting
XGBoost is a fast tree-based version of Gradient Boosting.
Decision Tree
XGBoost often uses decision trees as base models and fixes errors one tree at a time.
Ensemble
XGBoost combines many weak trees into one stronger predictor.
Supervised Learning
XGBoost often uses labeled data for classification and regression.