A new clustering algorithm applying a hierarchical method neural network

Abstract Clustering is a branch of multivariate analysis that is used to create groups of data. While there are currently a variety of techniques that are used for creating clusters, many require defining additional information, including the actual number of clusters, before they can be carried out. The case study of this research presents a novel neural network that is capable of creating groups by using a combination of hierarchical clustering and self-organizing maps, without requiring the number of existing clusters to be specified beforehand. Key words: Clustering, SOM, hierarchical clustering, PAM, Dendrogram, 1. Introduction Cluster analysis is a branch of multivariate statistical analysis that is used for detecting patterns in the classification of elements. Cluster analysis is used in a wide variety of fields including bioinformatics [9] [19] and surveillance [14] [15]. The methods used for clustering differ considerably according to the type of data and the amount of available information. Clustering techniques are typically broken down into the following categories [18] [19]