Totally Optimal Decision Trees for Monotone Boolean Functions with at Most Five Variables

In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct e...

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Bibliographic Details
Published in:	Procedia computer science Vol. 22; pp. 359 - 365
Main Authors:	Chikalov, Igor, Hussain, Shahid, Moshkov, Mikhail
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 2013
Subjects:	monotone Boolean functions number of nodes and depth of decision trees Totally optimal decision trees number of nodes and depth of decision trees monotone Boolean functions Totally optimal decision trees
ISSN:	1877-0509, 1877-0509
Online Access:	Get full text
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Summary:	In this paper, we present the empirical results for relationships between time (depth) and space (number of nodes) complexity of decision trees computing monotone Boolean functions, with at most five variables. We use Dagger (a tool for optimization of decision trees and decision rules) to conduct experiments. We show that, for each monotone Boolean function with at most five variables, there exists a totally optimal decision tree which is optimal with respect to both depth and number of nodes.
ISSN:	1877-0509 1877-0509
DOI:	10.1016/j.procs.2013.09.113