Gradient Boosting: Serial Self-Correction

Bagging grows independent trees in parallel and votes. Boosting grows trees in sequence — each one trained to fix what the ensemble currently gets wrong.

The ensemble predicts, the errors are measured, and the next small tree is fit to those residuals — literally answering 'where are we still wrong?' Add it to the ensemble, re-measure, repeat for hundreds of rounds.