Clustering Neutrosophic Data Sets and Neutrosophic Valued Metric Spaces


Tas F. , Topal S., Smarandache F.

SYMMETRY-BASEL, vol.10, no.10, 2018 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 10 Issue: 10
  • Publication Date: 2018
  • Doi Number: 10.3390/sym10100430
  • Title of Journal : SYMMETRY-BASEL

Abstract

In this paper, we define the neutrosophic valued (and generalized or G) metric spaces for the first time. Besides, we newly determine a mathematical model for clustering the neutrosophic big data sets using G-metric. Furthermore, relative weighted neutrosophic-valued distance and weighted cohesion measure, is defined for neutrosophic big data set. We offer a very practical method for data analysis of neutrosophic big data although neutrosophic data type (neutrosophic big data) are in massive and detailed form when compared with other data types.