Minimizing Number of Nodes in Decision Trees with Hypotheses

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Article
Authors
Azad, Mohammad
Chikalov, Igor
Hussain, Shahid
Moshkov, Mikhail cc
KAUST Department
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Extensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
Date
2021
Permanent link to this record
http://hdl.handle.net/10754/672059

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Abstract
In this paper, we consider decision trees that use both conventional queries based on one attribute each and queries based on hypotheses about values of all attributes. This approach is similar to one studied in exact learning, where membership and equivalence queries are considered. We propose dynamic programming algorithms for the minimization of the number of nodes in such decision trees and discuss results of computer experiments.
Citation
Azad, M., Chikalov, I., Hussain, S., & Moshkov, M. (2021). Minimizing Number of Nodes in Decision Trees with Hypotheses. Procedia Computer Science, 192, 232–240. doi:10.1016/j.procs.2021.08.024
Sponsors
Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST). The authors are greatly indebted to anonymous reviewers for useful comments and suggestions.
Publisher
Elsevier BV
Journal
Procedia Computer Science
DOI
10.1016/j.procs.2021.08.024
Additional Links
https://linkinghub.elsevier.com/retrieve/pii/S1877050921015118
Collections
Articles; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.
Except where otherwise noted, this item's license is described as This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.