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.

Simplifying decision trees by pruning and grafting: New results

ESPOSITO, Floriana;SEMERARO, Giovanni
1995

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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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/67873
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