Abstract
This paper presents an algorithm to prune a tree classifier with a set of rules which are converted from a C4.5 classifier, where rule information is used as a pruning criterion. Rule information measures the goodness of a rule when discriminating labeled instances. Empirical results demonstrate that the proposed pruning algorithm has high predictive accuracy.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zhang, X., Luo, M., Pi, D. (2005). Effective Classifier Pruning with Rule Information. In: Hoffmann, A., Motoda, H., Scheffer, T. (eds) Discovery Science. DS 2005. Lecture Notes in Computer Science(), vol 3735. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11563983_40
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DOI: https://doi.org/10.1007/11563983_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29230-2
Online ISBN: 978-3-540-31698-5
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