- Bilge International Journal of Science and Technology Research
- Volume:3 Special Issue
- A Data Classification Method in Machine Learning Based on Normalised Hamming Pseudo-Similarity of Fu...
A Data Classification Method in Machine Learning Based on Normalised Hamming Pseudo-Similarity of Fuzzy Parameterized Fuzzy Soft Matrices
Authors : Samet MEMİŞ, Serdar ENGİNOĞLU, Uğur ERKAN
Pages : 1-8
Doi:10.30516/bilgesci.643821
View : 64 | Download : 20
Publication Date : 2019-12-31
Article Type : Research Paper
Abstract :In this study, we propose a classification method based on normalised Hamming pseudo-similarity of fuzzy parameterized fuzzy soft matrices insert ignore into journalissuearticles values( fpfs -matrices);. We then compare the proposed method with Fuzzy Soft Set Classifier insert ignore into journalissuearticles values(FSSC);, FussCyier, Fuzzy Soft Set Classification Using Hamming Distance insert ignore into journalissuearticles values(HDFSSC);, and Fuzzy k-Nearest Neighbor insert ignore into journalissuearticles values(Fuzzy kNN); in terms of the performance criterions insert ignore into journalissuearticles values(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 insert ignore into journalissuearticles values(Diagnostic);”, “Immunotherapy”, “Pima Indian Diabetes”, and “Statlog Heart”.Keywords : Fuzzy Sets, Soft Sets, fpfs Matrices, Similarity Measure, Data Classification
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