A theoretical framework for decision trees in uncertain domains: Application to medical data sets

Experimental evidence shows that many attribute selection criteria involved in the induction of decision trees perform comparably. We set up a theoretical framework that explains this empirical law. It furthermore provides an infinite set of criteria (the C.M. criteria) which contains the most commo...

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Bibliographische Detailangaben

Hauptverfasser:	Crémilleux, B., Robert, C.
Format:	Buchkapitel
Sprache:	eng
Schlagworte:	Classification Error Rate Decision Tree Decision Tree Induction Nest Tree Pruning Method
Online-Zugang:	Volltext
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