Hybrid feature selection methods for online biomedical publication classification

Long Ma, Yanqing Zhang, Raj Sunderraman, Peter T Fox, Angela R. Laird, Jessica A. Turner, Matthew D. Turner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We review several feature selection methods: Recursive Feature Elimination, Select K Best, and Random Forests, as elements of a processing chain for feature selection in a text mining task. The text mining task is a multi-label classification problem of label assignment; metadata that is usually applied to published scientific papers by expert curators. In the formulation of this classification task, a feature space that is dramatically larger than the available training data occurs naturally and inevitably. We explore ways to reduce the dimension of the feature space, and show that sequential feature selection does substantially improve performance for this complex type of data.

Original languageEnglish (US)
Title of host publication2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479969265
DOIs
StatePublished - Oct 16 2015
EventIEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015 - Niagara Falls, Canada
Duration: Aug 12 2015Aug 15 2015

Other

OtherIEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015
CountryCanada
CityNiagara Falls
Period8/12/158/15/15

Keywords

  • feature selection
  • hybrid feature selection
  • metadata annotation
  • multi-label classification
  • text mining

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Health Informatics
  • Artificial Intelligence
  • Biomedical Engineering

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  • Cite this

    Ma, L., Zhang, Y., Sunderraman, R., Fox, P. T., Laird, A. R., Turner, J. A., & Turner, M. D. (2015). Hybrid feature selection methods for online biomedical publication classification. In 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2015 [7300320] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CIBCB.2015.7300320