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Artificial Neural Networks pp 226–243Cite as

The Extraction of Information and Knowledge from Trained Neural Networks

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Part of the book series: Methods in Molecular Biology™ ((MIMB,volume 458))

Abstract

In the past, neural networks were viewed as classification and regression systems whose internal representations were incomprehensible. It is now becoming apparent that algorithms can be designed that extract comprehensible representations from trained neural networks, enabling them to be used for data mining and knowledge discovery, that is, the discovery and explanation of previously unknown relationships present in data. This chapter reviews existing algorithms for extracting comprehensible representations from neural networks and outlines research to generalize and extend the capabilities of one of these algorithms, TREPAN. This algorithm has been generalized for application to bioinformatics data sets, including the prediction of splice site junctions in human DNA sequences, and cheminformatics. The results generated on these data sets are compared with those generated by a conventional data mining technique (C5) and appropriate conclusions are drawn.

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Acknowledgement

This chapter is dedicated to our dear friend and colleague, Martyn, who passed away after a brave fight with cancer on June 7, 2007.

Author information

Authors and Affiliations

  1. ChemQuest, Sandown, UK and Centre for Molecular Design, University of Portsmouth, Portsmouth, Hampshire, UK

    David J. Livingstone CChem FRSC

  2. Department of Computing, School of Engineering and Physical Sciences, University of Surrey, Guildford, Surrey, UK

    Antony Browne Dr.

  3. Centre for Molecular Design, University of Portsmouth, Portsmouth, Hampshire, UK

    Raymond Crichton

  4. Centre for Molecular Design, University of Portsmouth, Portsmouth, PO1 2DY, Hampshire, UK

    Brian D. Hudson BSc, PhD

  5. Centre for Molecular Design, University of Portsmouth, Portsmouth, Hampshire, UK

    David Whitley Dr.

Authors
  1. David J. Livingstone CChem FRSC
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  2. Antony Browne Dr.
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  3. Raymond Crichton
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  4. Brian D. Hudson BSc, PhD
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  5. David Whitley Dr.
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  6. Martyn G. Ford
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Corresponding author

Correspondence to Brian D. Hudson BSc, PhD .

Editor information

Editors and Affiliations

  1. ChemQuest, Sandown, Isle of Wight, United Kingdom, PO36 8LZ, UK

    David J. Livingstone

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© 2008 Humana Press, a part of Springer Science + Business Media, LLC

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Livingstone, D.J., Browne, A., Crichton, R., Hudson, B.D., Whitley, D., Ford, M.G. (2008). The Extraction of Information and Knowledge from Trained Neural Networks. In: Livingstone, D.J. (eds) Artificial Neural Networks. Methods in Molecular Biology™, vol 458. Humana Press. https://doi.org/10.1007/978-1-60327-101-1_12

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  • DOI: https://doi.org/10.1007/978-1-60327-101-1_12

  • Publisher Name: Humana Press

  • Print ISBN: 978-1-58829-718-1

  • Online ISBN: 978-1-60327-101-1

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