Efficient Modeling of Deterministic Decision Trees for Recognition of Realizable Decision Rules: Bounds on Weighted Depth

In this paper, an efficient algorithm for modeling the operation of a DDT (Deterministic Decision Tree) solving the problem of realizability of DRs (Decision Rules) is proposed and analyzed. For this problem, it is assumed that a DRS (Decision Rule System) is given; for an arbitrary tuple of feature...

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Veröffentlicht in:Axioms Jg. 14; H. 11; S. 794
Hauptverfasser: Durdymyradov, Kerven, Moshkov, Mikhail
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 01.11.2025
Schlagworte:
Algorithms
Analysis
Decision trees
Decision-making
deterministic decision tree
Modelling
nondeterministic decision tree
Realizability
system of decision rules
weighted depth
United States
ISSN:2075-1680, 2075-1680
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Zusammenfassung:In this paper, an efficient algorithm for modeling the operation of a DDT (Deterministic Decision Tree) solving the problem of realizability of DRs (Decision Rules) is proposed and analyzed. For this problem, it is assumed that a DRS (Decision Rule System) is given; for an arbitrary tuple of feature values, it is required to recognize whether there is a DR realizable on this tuple, i.e., a DR for which the left-hand side is true on the tuple. It is shown that the weighted depth of the modeled DDT does not exceed the square of the minimum weighted depth of the NDT (Nondeterministic Decision Tree) solving the realizability problem.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2075-1680
2075-1680
DOI:10.3390/axioms14110794