NS-k-NN: Neutrosophic Set-Based k-Nearest Neighbors Classifier
Author | : Yaman Akbulut |
Publisher | : Infinite Study |
Total Pages | : 10 |
Release | : |
ISBN-10 | : |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book NS-k-NN: Neutrosophic Set-Based k-Nearest Neighbors Classifier written by Yaman Akbulut and published by Infinite Study. This book was released on with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: k-nearest neighbors (k-NN), which is known to be a simple and efficient approach, is a non-parametric supervised classifier. It aims to determine the class label of an unknown sample by its k-nearest neighbors that are stored in a training set. The k-nearest neighbors are determined based on some distance functions. Although k-NN produces successful results, there have been some extensions for improving its precision. The neutrosophic set (NS) defines three memberships namely T, I and F. T, I, and F shows the truth membership degree, the false membership degree, and the indeterminacy membership degree, respectively. In this paper, the NS memberships are adopted to improve the classification performance of the k-NN classifier.