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Learning Classifier Systems Applied to Knowledge Discovery in Clinical Research Databases

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Learning Classifier Systems (IWLCS 1999)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1813))

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Abstract

A stimulus-response learning classifier system (LCS), EpiCS, was developed from the BOOLE and NEWBOOLE models to address the needs of knowledge discovery in databases used in clinical research. Two specific needs were investigated: the derivation of accurate estimates of disease risk, and the ability to deal with rare clinical outcomes. EpiCS was shown to have excellent classification accuracy, compared to logistic regression, when using risk estimates as the primary means for classification. This was especially true in data with low disease prevalence. EpiCS was designed to accommodate differential negative reinforcement when false positive or false negative decisions were made by the system. This feature was investigated to determine its effect on learning rate and classification accuracy. Tested across a range of disease prevalences, the learning rate improved when erroneous decisions were differentially negatively reinforced. However, classification accuracy was not affected by differential negative reinforcement

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Author information

Authors and Affiliations

  1. Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, USA

    John H. Holmes

Authors
  1. John H. Holmes
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Editor information

Editors and Affiliations

  1. Dipartimento di Elettronica ed Informatzione, Politecnico di Milano, Piazza Leonardo da Vinci n. 32, 20133, Milano, Italy

    Pier Luca Lanzi

  2. Institut für Psychologie III, Universität Würzburg, Röntgenring 11, 97070, Würzburg, Germany

    Wolfgang Stolzmann

  3. Prediction Dynamics, Concord, MA, 01742, USA

    Stewart W. Wilson

  4. Department of General Engineering, University of Illinois at Urbana-Champaign, USA

    Stewart W. Wilson

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© 2000 Springer-Verlag Berlin Heidelberg

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Holmes, J.H. (2000). Learning Classifier Systems Applied to Knowledge Discovery in Clinical Research Databases. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds) Learning Classifier Systems. IWLCS 1999. Lecture Notes in Computer Science(), vol 1813. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45027-0_13

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  • DOI: https://doi.org/10.1007/3-540-45027-0_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-67729-1

  • Online ISBN: 978-3-540-45027-6

  • eBook Packages: Springer Book Archive

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