Classification Based on Structural Information in Data

Basit Öğe Kaydı
dc.authoridArslan, Guvenc/0000-0002-4770-2689
dc.contributor.authorKarabulut, Bergen
dc.contributor.authorArslan, Guvenc
dc.contributor.authorUnver, Halil Murat
dc.date.accessioned2025-01-21T16:36:34Z
dc.date.available2025-01-21T16:36:34Z
dc.date.issued2022
dc.departmentKırıkkale Üniversitesi
dc.description.abstractClustering provides structural information from unlabeled data. The studies in which the structural information of the dataset is obtained through unsupervised learning approaches such as clustering and then transferred to the supervised learning are noteworthy. In this study, we propose a new preprocessing method, which obtains structural information that is expected to represent the most meaningful summary of the training dataset before applying a supervised learning strategy. To obtain this summary, the CURE clustering method was used. The proposed preprocessing method combined with SVM and a new classification method named representative points based SVM (RP-SVM) was developed. This new method was experimentally tested with various real datasets and was compared with the standard SVM, KMSVM, KNN and CART methods. The RP-SVM has significantly reduced the training size and resulted in less support vectors compared to standard SVM while achieving similar accuracy results. The RP-SVM has achieved better accuracy with less training data compared to KNN and CART. In addition, the RP-SVM has less data reduction compared to the KMSVM, but it is a more stable method that performs well in all datasets used. The results show that the proposed method can extract structural information that provides high quality for classification.
dc.identifier.doi10.1007/s13369-021-06177-3
dc.identifier.endpage2253
dc.identifier.issn2193-567X
dc.identifier.issn2191-4281
dc.identifier.issue2
dc.identifier.scopus2-s2.0-85115170180
dc.identifier.scopusqualityQ1
dc.identifier.startpage2239
dc.identifier.urihttps://doi.org/10.1007/s13369-021-06177-3
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24338
dc.identifier.volume47
dc.identifier.wosWOS:000698091100006
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofArabian Journal For Science and Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241229
dc.subjectCURE clustering algorithm; Natural structures; Representative points; Structural information; Support vector machines
dc.titleClassification Based on Structural Information in Data
dc.typeArticle

Dosyalar

Koleksiyon

WOS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu