Enhanced nearest centroid model tree classifer

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dc.authorid0000-0002-8339-7706
dc.authorid0000-0001-5176-6186
dc.authorid0000-0002-5561-4283
dc.authorid0000-0002-4815-4389
dc.contributor.authorÖzçelik, Mehmet Hamdi
dc.contributor.authorDuman, Ekrem
dc.contributor.authorBağrıyanık, Selami
dc.contributor.authorBulkan, Serol
dc.date.accessioned2025-05-12T09:09:04Z
dc.date.available2025-05-12T09:09:04Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik ve Doğa Bilimleri Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractIn this study, frst, we improved an existing variant of the Nearest Centroid algorithm. In this new version, the predic tive power of features and within-class variances are used as weights in distance calculation. This version is called the Enhanced Nearest Centroid (ENC). Second, we proposed a new model tree algorithm for binary classifcation. It is named as the Enhanced Nearest Centroid Model Tree (ENCMT). The model tree is built using ENC at each leaf node of the decision tree. To evaluate the performance of the new model tree, we used an independent test platform and ran the algorithm on 30 binary datasets available therein. Results showed that ENCMT improves the performance of the decision tree algorithm. We also compared ENCMT with the Logistic Model Tree (LMT) algorithm and showed that it outperforms LMT as well. We also designed a bagging algorithm where ENCMT is used to build a random forest. Our comparison results show that its performance is signifcantly better than the Random Forest (RF) algorithm.
dc.identifier.citationÖzçelik, M. H., Duman, E., Bağrıyanık, S., & Bulkan, S. (2025). Enhanced nearest centroid model tree classifer. Discover Computing, 28, https://doi.org/10.1007/s10791-025-09561-x
dc.identifier.doi10.1007/s10791-025-09561-x
dc.identifier.issn2948-2992
dc.identifier.urihttps://doi.org/10.1007/s10791-025-09561-x
dc.identifier.urihttps://hdl.handle.net/20.500.13055/980
dc.identifier.volume28
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynak.otherSCI-E - Science Citation Index Expanded
dc.institutionauthorBağrıyanık, Selami
dc.institutionauthorid0000-0002-5561-4283
dc.language.isoen
dc.publisherSpringer Nature Link
dc.relation.ispartofDiscover Computing
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBinary Classifcation
dc.subjectNearest Centroid Classifer
dc.subjectModel Tree
dc.subjectInformation Value
dc.titleEnhanced nearest centroid model tree classifer
dc.typeArticle
dspace.entity.typePublication

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