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, 3:O15 | Cite as

Feature selection in Enose applications

  • Thomas Nowotny
  • Amalia Z Berna
  • Russell Binions
  • X Rosalind Wang
  • Joseph T Lizier
  • Mikhail Prokopenko
  • Stephen Trowell
Open Access
Oral presentation
  • 739 Downloads

Keywords

Public Health Physical Chemistry Classification System Feature Selection Research Area 

In my presentation I will summarise results for feature selection from a number of Enose applications ranging from general chemical classification and breath analysis with metal-oxide based Enoses to work scoping the use of biological receptors, in particular receptors of the fruit fly Drosophila, for applications in wine making and explosives detection. The common thread in all applications is the availability of high-dimensional data which is often noisy and in all of its details not necessarily very information rich for any particular application. The challenge for building useful classification systems is to define, extract and select the most "informative" features from the high-dimensional data. I will give an overview over our work using exhaustive "wrapper" approaches and a brief comparison to information-theory based methods. I will conclude by highlighting the most pertinent open questions encountered in this research area.

Copyright information

© Nowotny et al; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Thomas Nowotny
    • 1
    • 2
  • Amalia Z Berna
    • 2
  • Russell Binions
    • 3
  • X Rosalind Wang
    • 4
  • Joseph T Lizier
    • 4
  • Mikhail Prokopenko
    • 4
  • Stephen Trowell
    • 2
  1. 1.CCNR, School of Engineering and InformaticsUniversity of SussexFalmerUK
  2. 2.CSIRO Ecosystem Sciences and Food Futures FlagshipAustralia
  3. 3.School of Engineering and Materials ScienceQueen Mary University of LondonLondon E1 4NSUK
  4. 4.CSIRO Information and Communications Technologies CentreEppingAustralia

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