A classification method based on Hamming pseudo-similarity of intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices

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dc.contributor.authorMemiş, Samet
dc.contributor.authorArslan, Burak
dc.contributor.authorAydın, Tuğçe
dc.contributor.authorEnginoğlu, Serdar
dc.contributor.authorCamcı, Çetin
dc.date.accessioned2025-05-29T05:38:32Z
dc.date.available2025-05-29T05:38:32Z
dc.date.issued2021
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.descriptionFHD-2020-3465
dc.description.abstractIn this study, firstly, Hamming pseudo-similarity of intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices (ifpifs-matrices) have been defined. Afterwards, a classifier based on Hamming pseudo-similarity of ifpifs-matrices (IFPIFS-HC) has been developed. The classifier's simulations have been performed using datasets provided in the UCI Machine Learning Database, and its performance results via the performance metrics accuracy, precision, recall, macro F-score, and micro F-score have been obtained. Thereafter, the results have been compared with those of the well-known methods. Then, the statistical evaluations of the performance results have been conducted using Friedman and Nemenyi post-hoc tests, and the critical diagrams of the Nemenyi post-hoc test are presented. The results and the statistical evaluations show that the proposed classifier has performed better than the others in 12 of 21 datasets in terms of the five performance metrics, in 4 of 21 in terms of the four performance metrics, and 17 of 21 in terms of accuracy performance metric. Moreover, the mean accuracy, precision, recall, precision, macro F-score, and micro F-score results of Fuzzy kNN, FSSC, FussCyier, HDFSSC, and FPFS-EC for the 21 datasets are 84.90, 71.96, 67.95, 71.91, and 75.28; 78.12, 68.01, 68.05, 66.53, and 67.68; 80.76, 68.63, 69.07, 68.36, and 70.65; 81.93, 69.43, 69.95, 70.25, and 72.36; and 89.59, 80.27, 78.40, 81.20, and 83.60, while those of IFPIFS-HC are 90.59, 82.88, 80.75, 82.89, and 85.48, respectively. Finally, the applications of ifpifs-matrices to machine learning have been discussed for further research.
dc.description.sponsorshipÇanakkale Onsekiz Mart University
dc.identifier.endpage76
dc.identifier.issn1304-7981
dc.identifier.issue2
dc.identifier.startpage59
dc.identifier.urihttps://hdl.handle.net/20.500.12428/31879
dc.identifier.volume10
dc.language.isoen
dc.publisherTokat Gaziosmanpasa University
dc.relation.ispartofJournal of New Results in Science
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_DergiPark_20250529
dc.subjectSoft sets
dc.subjectIntuitionistic fuzzy sets
dc.subjectifpifs-sets
dc.subjectifpifs-matrices
dc.subjectSimilarity measures
dc.subjectMachine learning
dc.titleA classification method based on Hamming pseudo-similarity of intuitionistic fuzzy parameterized intuitionistic fuzzy soft matrices
dc.typeResearch Article

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