Ensemble learning

statistical algorithm that is used to cluster points of data in functional groups

in machine learning, the use of multiple algorithms to obtain better predictive performance than from any of the constituent learning algorithms alone

ensemble meta-algorithm for reducing bias and variance in machine learning

machine learning technique

ensemble method within machine learning

AdaBoost (short for Adaptive Boosting) is a statistical classification meta-algorithm formulated by Yoav Freund and Robert Schapire in 1995, who won the 2003 Gödel Prize for their work. It can be used in conjunction with many types of learning algorithm to improve performance. The output of multiple weak learners is combined into a weighted sum that represents the final output of the boosted classifier. Usually, AdaBoost is presented for binary classification, although it can be generalized to multiple classes or bounded intervals of real values.