Linguistic K-Nearest Prototype
Abstract
In this chapter, a linguistic nearest prototype is firstly described, followed by a linguistic K-nearest prototype classifiers. Both classifiers work with vectors of fuzzy numbers and are applied to analyze management questionnaire data. Both classifiers employ the fuzzy distance calculations mentioned in Chapter 1. To find the closest prototype of K closest prototypes, all ranking methods described here are used in the algorithms. Although, in the examples, the centroid ranking method is used, we all know that using a different ranking method will certainly provide a different result.
Fields of Study & Subjects
Fuzzy Logic and Control Systems
Advanced Clustering Algorithms Research
Multi-Criteria Decision Making
Publication details
- Journal / source
- CRC Press eBooks
- Pages
- 20–33
- Publication date
- 6 March 2026
- Language
- EN
- Document type
- Book chapter