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Authors: Kerven Durdymyradov and Mikhail Moshkov

Affiliation: Computer, Electrical and Mathematical Sciences & Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia

Keyword(s): Algorithms, Decision Trees, Decision Rule Systems.

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 perfor mance of the three algorithms and evaluate their outcomes against the optimal results generated by the dynamic programming algorithm. (More)

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Paper citation in several formats:
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 - KDIR; ISBN ; ISSN 2184-3228, SciTePress, pages 173-180. DOI: 10.5220/0013533300004000

@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 - KDIR},
year={2025},
pages={173-180},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013533300004000},
isbn={},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR
TI - Experimental Study of Algorithms for Transforming Decision Rule Systems into Decision Trees
SN -
IS - 2184-3228
AU - Durdymyradov, K.
AU - Moshkov, M.
PY - 2025
SP - 173
EP - 180
DO - 10.5220/0013533300004000
PB - SciTePress

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