Experimental Study of Algorithms for Transforming Decision Rule Systems into Decision Trees

Kerven Durdymyradov, Mikhail Moshkov

2025

Abstract

The examination of the relationships between decision trees and systems of decision rules represents a significant area of research within computer science. While methods for converting decision trees into systems of decision rules are well-established and straightforward, the inverse transformation problem presents considerable challenges. Our previous work has demonstrated that the complexity of constructing complete decision trees can be superpolynomial in many cases. In our book, we proposed three polynomial time algorithms that do not construct the entire decision tree but instead outline the computation path within this tree for a specified input. Additionally, we introduced a dynamic programming algorithm that calculates the minimum depth of a decision tree corresponding to a given decision rule system. In the present paper, we describe these algorithms and the theoretical results obtained in the book. The primary objective of this paper is to experimentally compare the performance of the three algorithms and evaluate their outcomes against the optimal results generated by the dynamic programming algorithm.

Paper Citation

in Harvard Style

Durdymyradov K. and Moshkov M. (2025). Experimental Study of Algorithms for Transforming Decision Rule Systems into Decision Trees. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 173-180. DOI: 10.5220/0013533300004000

in Bibtex Style

@conference{kdir25,
author={Kerven Durdymyradov and Mikhail Moshkov},
title={Experimental Study of Algorithms for Transforming Decision Rule Systems into Decision Trees},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={173-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013533300004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Experimental Study of Algorithms for Transforming Decision Rule Systems into Decision Trees
SN -
AU - Durdymyradov K.
AU - Moshkov M.
PY - 2025
SP - 173
EP - 180
DO - 10.5220/0013533300004000
PB - SciTePress