Definition
An ensemble method that sequentially combines multiple weak learning models into a single strong predictor, with each new model focusing on correcting the errors of the previous ones.
In short: An ensemble method that sequentially combines multiple weak learning models into a single strong predictor, with each new model focusing on correcting the errors of the previous ones.