Building simple models: A case study with decision trees

David Jensen, Tim Oates, Paul R. Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations


Building correctly-sized models is a central challenge for induction algorithms. Many approaches to decision tree induction fail this challenge. Under a broad range of circumstances, these approaches exhibit a nearly linear relationship between training set size and tree size, even after accuracy has ceased to increase. These algorithms fail to adjust for the statistical effects of comparing multiple subtrees. Adjusting for these effects produces trees with little or no excess structure.

Original languageEnglish (US)
Title of host publicationAdvances in Intelligent Data Analysis
Subtitle of host publicationReasoning about Data - 2nd International Symposium, IDA-1997, Proceedings
EditorsXiaohui Liu, Paul Cohen, Michael Berthold
Number of pages12
ISBN (Print)9783540633464
StatePublished - 1997
Externally publishedYes
Event2nd International Symposium on Intelligent Data Analysis, IDA 1997 - London, United Kingdom
Duration: Aug 4 1997Aug 6 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other2nd International Symposium on Intelligent Data Analysis, IDA 1997
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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