Adaboost, short for Adaptive Boosting, is a machine learning algorithm that is used to improve the performance of classification models. It combines multiple weak classifiers to create a strong classifier. This ensemble method focuses on instances that are hard to classify by assigning higher weights to them in subsequent classifiers.
