A Data Classification Method in Machine Learning Based on Normalised Hamming Pseudo-Similarity of Fuzzy Parameterized Fuzzy Soft Matrices

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dc.contributor.authorMemiş, Samet
dc.contributor.authorEnginoğlu, Serdar
dc.contributor.authorErkan, Uğur
dc.date.accessioned2025-05-29T05:24:31Z
dc.date.available2025-05-29T05:24:31Z
dc.date.issued2019
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractIn this study, we propose a classification method based on normalised Hamming pseudo-similarity of fuzzy parameterized fuzzy soft matrices (fpfs-matrices). We then compare the proposed method with Fuzzy Soft Set Classifier (FSSC), FussCyier, Fuzzy Soft Set Classification Using Hamming Distance (HDFSSC), and Fuzzy k-Nearest Neighbor (Fuzzy kNN) in terms of the performance criterions (accuracy, precision, recall, and F-measure) and running time by using four medical data sets in the UCI machine learning repository. The results show that the proposed method performs better than FSSC, FussCyier, HDFSSC, and Fuzzy kNN for “Breast Cancer Wisconsin (Diagnostic)”, “Immunotherapy”, “Pima Indian Diabetes”, and “Statlog Heart”.
dc.identifier.doi10.30516/bilgesci.643821
dc.identifier.issn2651-401X
dc.identifier.issn2651-4028
dc.identifier.issue0
dc.identifier.startpage8-Jan
dc.identifier.urihttps://doi.org/10.30516/bilgesci.643821
dc.identifier.urihttps://hdl.handle.net/20.500.12428/30869
dc.identifier.volume3
dc.language.isoen
dc.publisherKutbilge Akademisyenler Derneği
dc.relation.ispartofBilge International Journal of Science and Technology Research
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250529
dc.subjectFuzzy Sets
dc.subjectSoft Sets
dc.subjectfpfs-Matrices
dc.subjectSimilarity Measure
dc.subjectData Classification
dc.titleA Data Classification Method in Machine Learning Based on Normalised Hamming Pseudo-Similarity of Fuzzy Parameterized Fuzzy Soft Matrices
dc.typeResearch Article

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