Yet Another Induction Algorithm

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Title Yet Another Induction Algorithm
Author An, Jay; Chen, Yi-Ping Phoebe
Journal Name Lecture Notes in Computer Science
Year Published 2005
Place of publication Berlin
Publisher Springer
Abstract Inducing general functions from specific training examples is a central problem in the machine learning. Using sets of If-then rules is the most expressive and readable manner. To find If-then rules, many induction algorithms such as ID3, AQ, CN2 and their variants, were proposed. Sequential covering is the kernel technique of them. To avoid testing all possible selectors, Entropy gain is used to select the best attribute in ID3. Constraint of the size of star was introduced in AQ and beam search was adopted in CN2. These methods speed up their induction algorithms but many good selectors are filtered out. In this work, we introduce a new induction algorithm that is based on enumeration of all possible selectors. Contrary to the previous works, we use pruning power to reduce irrelative selectors. But we can guarantee that no good selectors are filtered out. Comparing with other techniques, the experiment results demonstrate that the rules produced by our induction algorithm have high consistency and simplicity.
Peer Reviewed Yes
Published Yes
Alternative URI http://dx.doi.org/10.1007/11552451_6
Volume 3682
Page from 37
Page to 44
ISSN 0302-9743
Date Accessioned 2009-09-09
Date Available 2010-08-30T07:04:27Z
Language en_AU
Faculty Faculty of Science, Environment, Engineering and Technology
Subject PRE2009-Other Artificial Intelligence
URI http://hdl.handle.net/10072/25647
Publication Type Journal Articles (Refereed Article)
Publication Type Code c1x

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