1999 EnsembleLearningviaNegativeCorr

• (Yao & Liu, 1999) ⇒ X.Yao, and Y. Liu. (1999). “Ensemble Learning via Negative Correlation.” In: Neural Networks Journal, 12(10). doi:10.1016/S0893-6080(99)00073-8

Subject Headings: Negative Correlation Learning

Cited By

• http://scholar.google.com/scholar?q=%221999%22+Ensemble+Learning+via+Negative+Correlation
• http://dl.acm.org/citation.cfm?id=340217.340231&preflayout=flat#citedby

Quotes

Author Keywords

• Neural Network Ensembles; Negative Correlation Learning; Generalisation; Correlation; Combination Method; Correct Response Set,

Abstract

This paper presents a learning approach, i.e. negative correlation learning, for neural network ensembles. Unlike previous learning approaches for neural network ensembles, negative correlation learning attempts to train individual networks in an ensemble and combines them in the same learning process. In negative correlation learning, all the individual networks in the ensemble are trained simultaneously and interactively through the correlation penalty terms in their error functions. Rather than producing unbiased individual networks whose errors are uncorrelated, negative correlation learning can create negatively correlated networks to encourage specialisation and cooperation among the individual networks. Empirical studies have been carried out to show why and how negative correlation learning works. The experimental results show that negative correlation learning can produce neural network ensembles with good generalisation ability.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
1999 EnsembleLearningviaNegativeCorr	X.Yao Y. Liu			Ensemble Learning via Negative Correlation				10.1016/S0893-6080(99)00073-8		1999