Yayınlanmış 1 Ocak 2021
| Sürüm v1
Dergi makalesi
Açık
Numerical Data Classification via Distance-Based Similarity Measures of Fuzzy Parameterized Fuzzy Soft Matrices
Oluşturanlar
- 1. Canakkale Onsekiz Mart Univ, Fac Arts & Sci, Dept Math, TR-17100 Canakkale, Turkey
- 2. Karamanoglu Mehmetbey Univ, Fac Engn, Dept Comp Engn, TR-70100 Karaman, Turkey
Açıklama
In this paper, we first define eight pseudo-metrics and eight pseudo-similarities based on these pseudo-metrics overfpfs-matrices. We then propose a new classification algorithm, i.e. Fuzzy Parameterized Fuzzy Soft Euclidean Classifier (FPFS-EC), based on Euclidean pseudo-similarity. After that, we compare FPFS-EC with Support Vector Machines (SVM), Fuzzy k-Nearest Neighbor (Fuzzy kNN), Fuzzy Soft Set Classifier (FSSC), FussCyier, Fuzzy Soft Set Classification Using Hamming Distance (HDFSSC), and Fuzzy kNN Based on the Bonferroni Mean (BM-Fuzzy kNN) in terms of the performance criteria - namely accuracy, precision, recall, macro F-score, and micro F-score - and running time by using 18 real-world datasets in the UCI machine learning repository. The results show that FPFS-EC performs better in the occurrence of the 13 of 18 datasets in question than SVM, Fuzzy kNN, FSSC, FussCyier, HDFSSC, and BM-Fuzzy kNN.
Dosyalar
bib-6c5fe595-c390-4afe-91db-987d2ced99c2.txt
Dosyalar
(192 Bytes)
| Ad | Boyut | Hepisini indir |
|---|---|---|
|
md5:0c60df11ad9d46fb969f14e6e110a158
|
192 Bytes | Ön İzleme İndir |