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Simplifying decision trees by pruning and grafting: New results (Extended abstract)

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (1995) 912 287-290
DOI: 10.1007/3-540-59286-5_69
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Abstract

This paper presents some empirical results on simplification methods of decision trees induced from data. We observe that those methods exploiting an independent pruning set do not perform uniformly better than the others. Furthermore, a clear definition of bias towards overpruning and underpruning is exploited in order to interpret empirical data concerning the size of the simplified trees.

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APA

Esposito, F., Malerba, D., & Semeraro, G. (1995). Simplifying decision trees by pruning and grafting: New results (Extended abstract). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 912, pp. 287–290). Springer Verlag. https://doi.org/10.1007/3-540-59286-5_69

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