Algorithm for Clustering Data Set Represented by Intuitionistic Fuzzy Estimates

Abstract

One of the main problems in the area of pattern recognition in biomedical research areas is to determine clusters of patterns with similar features. It is especially relevant in the case of intuitionistic fuzzy sets. In the present paper an iterative procedure for clustering of patterns represented by their intuitionistic fuzzy sets - degrees of membership, degrees of non-membership and indeterminacy. The procedure is open to selection and application of an appropriate to the data distribution similarity measure for intuitionistic fuzzy sets.

Keywords

• Intuitionistic fuzzy sets
• Pattern recognition
• Distance
• Similarity measures between IFS