A new classification method using soft decision-making based on an aggregation operator of fuzzy parameterized fuzzy soft matrices

Basit Öğe Kaydı
dc.contributor.authorMemış, Samet
dc.contributor.authorEnginoğlu, Serdar
dc.contributor.authorErkan, Uğur
dc.date.accessioned2025-01-27T19:34:59Z
dc.date.available2025-01-27T19:34:59Z
dc.date.issued2022
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractRecently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass),\rhas been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest\rneighbours, support vector machines, and decision trees. In this paper, we offer a new classification algorithm called fuzzy\rparameterized fuzzy soft aggregation classifier (FPFS-AC) to combine the modelling ability of soft decision-making (SDM)\rand classification success of generalised eigenvalues. FPFS-AC constructs a decision matrix by employing the similarity\rmeasures of fuzzy parameterized fuzzy soft matrices (fpfs-matrices) and a generalised eigenvalue-based similarity measure.\rThen, it applies an SDM method based on the aggregation operator of fpfs-matrices to a decision matrix and classifies\rthe given test sample. Afterwards, we perform an experimental study using 15 UCI datasets to manifest the success\rof our approach and compare FPFS-AC with the well-known and state-of-the-art classifiers (kNN, SVM, fuzzy kNN,\rEigenClass, and BM-fuzzy kNN) in terms of accuracy, precision, recall, macro F-score, micro F-score, and running time.\rMoreover, we statistically analyse the experimentally obtained data. Experimental and statistical results show that\rFPFS-AC outperforms the state-of-the-art classifiers in all the datasets concerning the five performance metrics.
dc.identifier.doi10.3906/elk-2106-28
dc.identifier.endpage890
dc.identifier.issn1300-0632
dc.identifier.issn1300-0632
dc.identifier.issue3
dc.identifier.startpage871
dc.identifier.trdizinid528871
dc.identifier.urihttps://doi.org/10.3906/elk-2106-28
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/528871
dc.identifier.urihttps://hdl.handle.net/20.500.12428/16791
dc.identifier.volume30
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofTurkish Journal of Electrical Engineering and Computer Sciences
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TRD_20250125
dc.subjectBilgisayar Bilimleri
dc.subjectYazılım Mühendisliği
dc.titleA new classification method using soft decision-making based on an aggregation operator of fuzzy parameterized fuzzy soft matrices
dc.typeArticle

Dosyalar

Koleksiyon

TR-Dizin İndeksli Yayınlar Koleksiyonu