TY - JOUR
T1 - Minimizing Number of Nodes in Decision Trees with Hypotheses
AU - Azad, Mohammad
AU - Chikalov, Igor
AU - Hussain, Shahid
AU - Moshkov, Mikhail
N1 - KAUST Repository Item: Exported on 2021-10-04
Acknowledgements: 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.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/672059
UR - https://linkinghub.elsevier.com/retrieve/pii/S1877050921015118
U2 - 10.1016/j.procs.2021.08.024
DO - 10.1016/j.procs.2021.08.024
M3 - Article
SN - 1877-0509
VL - 192
SP - 232
EP - 240
JO - Procedia Computer Science
JF - Procedia Computer Science
ER -