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ICML
1998
IEEE

The Problem with Noise and Small Disjuncts

13 years 7 months ago
The Problem with Noise and Small Disjuncts
Many systems that learn from examples express the learned concept as a disjunction. Those disjuncts that cover only a few examples are referred to as small disjuncts. The problem with small disjuncts is that they have a much higher error rate than large disjuncts but are necessary to achieve a high level of predictive accuracy. This paper investigates the effect of noise on small disjuncts. In particular, we show that when noise is added to two real-world domains, a significant, and disproportionate number of the total errors are contributed by the small disjuncts; thus, in the presence of noise, it is the small disjuncts that are primarily responsible for the poor predictive accuracy of the learned concept.
Gary M. Weiss, Haym Hirsh
Added 24 Aug 2010
Updated 24 Aug 2010
Type Conference
Year 1998
Where ICML
Authors Gary M. Weiss, Haym Hirsh
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