Robust cutpoints in the logical analysis of numerical data

Martin Anthony, Joel Ratsaby

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Techniques for the logical analysis of binary data have successfully been applied to non-binary data which has been 'binarized' by means of cutpoints; see Boros et al. (1997, 2000) [7,8]. In this paper, we analyze the predictive performance of such techniques and, in particular, we derive generalization error bounds that depend on how 'robust' the cutpoints are.

Original languageEnglish
Pages (from-to)355-364
Number of pages10
JournalDiscrete Applied Mathematics
Issue number4-5
StatePublished - Mar 2012


  • Generalization error
  • LAD methods
  • Learning algorithms
  • Logical analysis of data
  • Machine learning


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