Ensemble learning by negative correlation learning

Huanhuan CHEN*, Anthony G. COHN, Xin YAO

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsBook ChapterResearchpeer-review

5 Citations (Scopus)

Abstract

This chapter investigates a specific ensemble learning approach by negative correlation learning (NCL) [21–23]. NCL is an ensemble learning algorithm which considers the cooperation and interaction among the ensemble members. NCL introduces a correlation penalty term into the cost function of each individual learner so that each learner minimizes its mean-square-error (MSE) error together with the correlation with other ensemble members.

Original languageEnglish
Title of host publicationEnsemble Machine Learning: Methods and Applications
EditorsCha ZHANG, Yunqian MA
PublisherSpringer New York
Pages177-201
Number of pages25
Edition1
ISBN (Electronic)9781441993267
ISBN (Print)9781441993250
DOIs
Publication statusPublished - 2012
Externally publishedYes

Bibliographical note

Publisher Copyright:
© Springer Science+Business Media, LLC 2012. All rights reserved.

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