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KDD
1994
ACM

A Comparison of Pruning Methods for Relational Concept Learning

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A Comparison of Pruning Methods for Relational Concept Learning
Pre-Pruning and Post-Pruning are two standard methods of dealing with noise in concept learning. Pre-Pruning methods are very efficient, while Post-Pruning methods typically are moreaccurate, but muchslower, because they have to generate an overly specific concept description first. Wehave experimented with a variety of pruning methods, including two new methods that try to combine and integrate pre- and postpruning in order to achieve both accuracy and efficiency. This is verified with test series in a chess position classification task.
Johannes Fürnkranz
Added 10 Aug 2010
Updated 10 Aug 2010
Type Conference
Year 1994
Where KDD
Authors Johannes Fürnkranz
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