Very Simple Classification Rules Perform Well on Most Commonly Used Datasets

Authors:
Robert C. Holte
Affiliations:
Computer Science Department, University of Ottawa, Ottawa, Canada KIN 6N5. HOLTE@CSI.UOTTAWA.CA
Venue:
Machine Learning
Year:
1993

Citing 0
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Abstract

This article reports an empirical investigation of the accuracy of rules that classify examples on the basis of a single attribute. On most datasets studied, the best of these very simple rules is as accurate as the rules induced by the majority of machine learning systems. The article explores the implications of this finding for machine learning research and applications.