 The resulting diagram from a Hierarchical Cluster Analysis is called a dendrogram, in which data are nested into brackets of increasing dissimilarity.Two common issues with Hierarchical Clustering include designating a specific distance of “similarity” between two data points, in order to generate meaningful associations between data points, and also how to merge data points, in a way that will be helpful for further clustering once they have been deemed similar.A cross-clustering algorithm with automatic estimation of the number of clusters has been designed, which helps resolve some of these issues.