Construction of Decision Trees and Acyclic Decision Graphs from Decision Rule Systems

dc.contributor.authorDurdymyradov, Kerven
dc.contributor.authorMoshkov, Mikhail
dc.contributor.departmentApplied Mathematics and Computational Science Program
dc.contributor.departmentComputational Bioscience Research Center (CBRC)
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.date.accessioned2023-05-25T11:57:02Z
dc.date.available2023-05-25T11:57:02Z
dc.date.issued2023-05-02
dc.description.abstractDecision trees and systems of decision rules are widely used as classifiers, as a means for knowledge representation, and as algorithms. They are among the most interpretable models for data analysis. The study of the relationships between these two models can be seen as an important task of computer science. Methods for transforming decision trees into systems of decision rules are simple and well-known. In this paper, we consider the inverse transformation problem, which is not trivial. We study the complexity of constructing decision trees and acyclic decision graphs representing decision trees from decision rule systems, and we discuss the possibility of not building the entire decision tree, but describing the computation path in this tree for the given input.
dc.description.sponsorshipResearch reported in this publication was supported by King Abdullah University of Science and Technology (KAUST).
dc.eprint.versionPre-print
dc.identifier.arxivid2305.01721
dc.identifier.urihttp://hdl.handle.net/10754/692062
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/2305.01721.pdf
dc.rightsThis is a preprint version of a paper and has not been peer reviewed. Archived with thanks to arXiv.
dc.titleConstruction of Decision Trees and Acyclic Decision Graphs from Decision Rule Systems
dc.typePreprint
display.details.left<span><h5>Type</h5>Preprint<br><br><h5>Authors</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.author=Durdymyradov, Kerven,equals">Durdymyradov, Kerven</a><br><a href="https://repository.kaust.edu.sa/search?query=orcid.id:0000-0003-0085-9483&spc.sf=dc.date.issued&spc.sd=DESC">Moshkov, Mikhail</a> <a href="https://orcid.org/0000-0003-0085-9483" target="_blank"><img src="https://repository.kaust.edu.sa/server/api/core/bitstreams/82a625b4-ed4b-40c8-865a-d6a5225a26a4/content" width="16" height="16"/></a><br><br><h5>KAUST Department</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.department=Applied Mathematics and Computational Science Program,equals">Applied Mathematics and Computational Science Program</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.department=Computational Bioscience Research Center (CBRC),equals">Computational Bioscience Research Center (CBRC)</a><br><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.department=Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division,equals">Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division</a><br><br><h5>Date</h5>2023-05-02</span>
display.details.right<span><h5>Abstract</h5>Decision trees and systems of decision rules are widely used as classifiers, as a means for knowledge representation, and as algorithms. They are among the most interpretable models for data analysis. The study of the relationships between these two models can be seen as an important task of computer science. Methods for transforming decision trees into systems of decision rules are simple and well-known. In this paper, we consider the inverse transformation problem, which is not trivial. We study the complexity of constructing decision trees and acyclic decision graphs representing decision trees from decision rule systems, and we discuss the possibility of not building the entire decision tree, but describing the computation path in this tree for the given input.<br><br><h5>Acknowledgements</h5>Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST).<br><br><h5>Publisher</h5><a href="https://repository.kaust.edu.sa/search?spc.sf=dc.date.issued&spc.sd=DESC&f.publisher=arXiv,equals">arXiv</a><br><br><h5>arXiv</h5><a href="https://arxiv.org/abs/2305.01721">2305.01721</a><br><br><h5>Additional Links</h5>https://arxiv.org/pdf/2305.01721.pdf</span>
kaust.personDurdymyradov, Kerven
kaust.personMoshkov, Mikhail
orcid.id0000-0003-0085-9483
refterms.dateFOA2023-05-25T11:57:35Z
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2305.01721.pdf
Size:
543.21 KB
Format:
Adobe Portable Document Format
Description:
Preprint