Boosting: Foundations and Algorithms 论文
2013Kybernetes引用 229
Face and Expression RecognitionNeural Networks and ApplicationsMachine Learning and Data Classification
摘要
Boosting is a general method for improving the accuracy of any given learning algorithm. This short overview paper introduces the boosting algorithm AdaBoost, and explains the underlying theory of boosting, including an explanation of why boosting often does not suffer from overfitting as well as boosting's relationship to support-vector machines. Some examples of recent applications of boosting are also described.