Skip to main content
SpringerLink
Log in

Generation of Boolean classification rules

  • Conference paper
COMPSTAT

  • 779 Accesses

Abstract

An algorithm to generate a class of Boolean classification rules is described. The algorithm is implemented in search partition analysis software (SPAN), a program designed to find an optimal binary data partition. Some comments on the relationship of the procedure with tree-based search procedures are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Broad, J., Marshall, R.J. and Bonita, R. (2000). The prediction of death soon after a stroke: A case study comparing four statistically derived prediction rules. Journal of Clinical Epidemiology (submitted).

    Google Scholar 

  • Gentleman, J.F. (1975). Algorithm AS 88. Generation of all n C r combinations by simulating nested Fortran DO loops. Applied Statistics, 24, 374–376.

    Article  Google Scholar 

  • Herman, W.H., Engelgau, M.M., Smith, P.J., Aubert, R.E. and Thompson, T.J. (1995). A new and simple questionnaire to identify people at increased risk for undiagnosed diabetes. Diabetes Care, 18,382–387.

    Article  Google Scholar 

  • Marshall, R.J. (1986). Partitioning methods for classification and decision making in medicine. Statistics in Medicine, 5, 517–526.

    Article  Google Scholar 

  • Marshall, R.J. (1995). A program to implement a search method for identification of clinical subgroups. Statistics in Medicine, 14, 2645–2660.

    Article  Google Scholar 

  • Marshall, R.J. (1999). Classification to ordinal categories using a search partition methodology with an application in diabetes screening. Statistics in Medicine, 20, 2723–2736.

    Article  Google Scholar 

  • Marshall, R.J. (2000). The use of classification and regression trees in clinical epidemiology. Journal of Clinical Epidemiology (in press)

    Google Scholar 

  • Pagallo, G. and Haussler, D. (1990). Boolean feature discovery and empirical learning. Machine Learning, 5, 71–99.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Community Health, University of Auckland, New Zealand

    Roger J. Marshall

Authors
  1. Roger J. Marshall
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Statistical Methods, Statistics Netherlands, P.O. Box 4000, 2270 JM, Voorburg, The Netherlands

    Jelke G. Bethlehem

  2. Faculty of Social Sciences, Department of Methodology and Statistics, Utrecht University, P.O. Box 80140, 3508 TC, Utrecht, The Netherlands

    Peter G. M. van der Heijden

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Marshall, R.J. (2000). Generation of Boolean classification rules. In: Bethlehem, J.G., van der Heijden, P.G.M. (eds) COMPSTAT. Physica, Heidelberg. https://doi.org/10.1007/978-3-642-57678-2_46

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-57678-2_46

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-1326-5

  • Online ISBN: 978-3-642-57678-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation