A Modified Similarity Measure for Continuous Function Valued Intuitionistic Fuzzy Sets and an Application on Classification

Aydoğan B., ÜNVER M.

8th International conference Approximation Theory and Special Functions, ATSF 2024, Ankara, Turkey, 4 - 07 September 2024, vol.503 PROMS, pp.511-523, (Full Text) identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 503 PROMS
  • Doi Number: 10.1007/978-3-031-93279-3_28
  • City: Ankara
  • Country: Turkey
  • Page Numbers: pp.511-523
  • Keywords: Continuous function valued intuitionistic fuzzy set, Fuzzy classification
  • Ankara University Affiliated: Yes

Abstract

Classification is a supervised machine learning task, whereby the objective is to predict the class or category of a given input based on a set of labeled examples. This method is employed for the reorganization of data into predefined classes in accordance with the specifications of designated algorithms. This work focuses on combining continuous function-valued intuitionistic fuzzy sets (CFVIFSs) with classification. By integrating CFVIFSs and classification, which represents a novel approach, the fuzzy classification method offers a novel perspective. Furthermore, a new similarity measure for CFVIFSs is defined and a distinct fuzzy classification solution logic is introduced using an aggregation operator.