Ensemble learning via negative correlation

Y. LIU, X. YAO

Research output: Journal PublicationsJournal Article (refereed)peer-review

570 Citations (Scopus)

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 specialization 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 generalization ability.; 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.
Original languageEnglish
Pages (from-to)1399-1404
Number of pages6
JournalNeural Networks
Volume12
Issue number10
DOIs
Publication statusPublished - Dec 1999
Externally publishedYes

Funding

sThe authors are grateful to anonymous referees for their constructive comments that have helped to improve the paper.

Keywords

  • Combination method
  • Correct response set
  • Correlation
  • Generalisation
  • Negative correlation learning
  • Neural network ensembles

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