Dynamic Adaboost ensemble extreme learning machine
Gaitang Wang, Ping Li · 2010
This paper proposes a new algorithm: dynamic Adaboost ensemble extreme learning machine, which regards the extreme learning machine as weak learning machine, dynamic Adaboost ensemble algorithm is used to integrate the outputs of weak learning machines, and makes use of fuzzy activation function as activation function of extreme learning machine because of low computational burden and easy implementation in hardware. Proposed algorithm has been successfully applied to problem of function approximation and classification application. Experimental results show that the algorithm increases the training speed greatly when dealing with large dataset and has better generalization performance than extreme learning machine algorithm and Boosting ensemble extreme learning machine with Quasi-Newton algorithm.