Look-ahead mechanism integration in decision tree induction models

Michael Roizman, Mark Last

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations


Most of decision tree induction algorithms use a greedy splitting criterion. One of the possible solutions to avoid this greediness is looking ahead to make better splits. Look-Ahead has not been used in most decision tree methods primarily because of its high computational complexity and its questionable contribution to predictive accuracy. In this paper we describe a new Look-Ahead approach to induction of decision tree models. We present a computationally efficient algorithm which evaluates quality of subtrees of variable-depth in order to determine the best split attribute out of a set of candidate attributes with a splitting criterion statistically indifferent from the best one.

Original languageEnglish
Title of host publicationAdvances in Web Intelligence and Data Mining
EditorsMark Last, Piotr Szczepaniak, Piotr Szczepaniak, Zeev Vlvolkov, Abraham Kandel
Number of pages10
StatePublished - 27 Sep 2006

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence


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