Regularized negative correlation learning for neural network ensembles

IEEE Transactions on Neural Networks
Huanhuan Chen, Xin Yao

Abstract

Negative correlation learning (NCL) is a neural network ensemble learning algorithm that introduces a correlation penalty term to the cost function of each individual network so that each neural network minimizes its mean square error (MSE) together with the correlation of the ensemble. This paper analyzes NCL and reveals that the training of NCL (when lambda = 1) corresponds to training the entire ensemble as a single learning machine that only minimizes the MSE without regularization. This analysis explains the reason why NCL is prone to overfitting the noise in the training set. This paper also demonstrates that tuning the correlation parameter lambda in NCL by cross validation cannot overcome the overfitting problem. The paper analyzes this problem and proposes the regularized negative correlation learning (RNCL) algorithm which incorporates an additional regularization term for the whole ensemble. RNCL decomposes the ensemble's training objectives, including MSE and regularization, into a set of sub-objectives, and each sub-objective is implemented by an individual neural network. In this paper, we also provide a Bayesian interpretation for RNCL and provide an automatic algorithm to optimize regularization parameters based...Continue Reading

References

Mar 29, 2003·Neural Networks : the Official Journal of the International Neural Network Society·Y Liu, X Yao
Feb 2, 2008·IEEE Transactions on Neural Networks·Md M IslamK Murase
Feb 7, 2008·IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society·Y Liu, X Yao
Feb 7, 2008·IEEE Transactions on Neural Networks·J Y Kwok
Apr 29, 2009·IEEE Transactions on Neural Networks·Huanhuan ChenXin Yao

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Citations

May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Francisco Fernández-NavarroXin Yao
May 9, 2014·IEEE Transactions on Neural Networks and Learning Systems·Huanhuan ChenXin Yao
Jul 1, 2012·IEEE Transactions on Neural Networks and Learning Systems·Haibo He, Yuan Cao
Dec 30, 2010·IEEE Transactions on Neural Networks·Pablo A Dalbem Castro, Fernando José Von Zuben
Apr 8, 2020·Computational and Structural Biotechnology Journal·Julian D SchwabHans A Kestler
Feb 14, 2021·Neural Networks : the Official Journal of the International Neural Network Society·Changqin HuangDianhui Wang

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