Exploiting ensemble diversity for automatic feature extraction

G. BROWN, Xin YAO, J. WYATT, H. WERSING, B. SENDHOFF

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

10 Citations (Scopus)

Abstract

We present an automatic method, based on a neural network ensemble, for extracting multiple, diverse and complementary sets of useful classification features from high-dimensional data. We demonstrate the utility of these diverse representations for an image dataset, showing good classification accuracy and a high degree of dimensionality reduction. We then outline a number of possible extensions to the project in an evolutionary computation context. © 2002 Nanyang Technological University.
Original languageEnglish
Title of host publicationICONIP 2002 - Proceedings of the 9th International Conference on Neural Information Processing: Computational Intelligence for the E-Age
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1786-1790
Number of pages5
Volume4
ISBN (Print)9789810475246
DOIs
Publication statusPublished - 27 Aug 2003
Externally publishedYes

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