Neutrosophic Logic-based DIANA Clustering algorithm

On the one hand, the most extensively used Hierarchical Clustering techniques are the Hierarchical Divisive Clustering (HDC) algorithms such as DIANA. Its primary goal is to build the tree of Hierarchical Agglomerative Clustering (HAC) in reverse order. On the other hand, Neutrosophy is an extension of fuzzy logic and serves as a model of uncertainty. In addition to the truth (T) and falsity (F) elements of fuzzy logic, single-valued Neutrosophic sets (SVNs) logic estimates the proportion of indeterminacy (I) for a given proposition. In this work, we propose a Neutrosophic Logic-based DIANA Clustering algorithm. Indeterminacy is added to the DIANA hierarchical clustering algorithm using single-valued Neutrosophic sets (SVNs). The suggested algorithm is named Neutro-DIANA (Neutrosophic DIANA) and is broken down into numerous steps. The experimental findings show that the suggested technique for dealing with indeterminacy is effective