ML Anthology

A New MDL Measure for Robust Rule Induction (Extended Abstract)

Bernhard Pfahringer
ECML-PKDD 1995 pp. 331-334
doi:10.1007/3-540-59286-5_80 /ecmlpkdd/1995/pfahringer1995ecml-new/

Abstract

We present a generalization of a particular Minimum Description Length (MDL) measure that so far has been used for pruning decision trees only. The generalized measure is applicable to (propositional) rule sets directly. Furthermore the new measure also does not suffer from problems reported for various MDL measures in the ML literature. The new measure is information-theoretically plausible and yet still simple and therefore efficiently computable. It is incorporated in a propositional Foil -like learner called Knopf .

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Cite

Text

Pfahringer. "A New MDL Measure for Robust Rule Induction (Extended Abstract)." European Conference on Machine Learning, 1995. doi:10.1007/3-540-59286-5_80

Markdown

[Pfahringer. "A New MDL Measure for Robust Rule Induction (Extended Abstract)." European Conference on Machine Learning, 1995.](https://mlanthology.org/ecmlpkdd/1995/pfahringer1995ecml-new/) doi:10.1007/3-540-59286-5_80

BibTeX

@inproceedings{pfahringer1995ecml-new,
  title     = {{A New MDL Measure for Robust Rule Induction (Extended Abstract)}},
  author    = {Pfahringer, Bernhard},
  booktitle = {European Conference on Machine Learning},
  year      = {1995},
  pages     = {331-334},
  doi       = {10.1007/3-540-59286-5_80},
  url       = {https://mlanthology.org/ecmlpkdd/1995/pfahringer1995ecml-new/}
}