A hierarchical approach to ART-like clustering algorithm

We propose a hierarchical approach to ART-like clustering algorithm which is able to deal with data consisting of arbitrarily geometrical-shaped clusters. A combined hierarchical and ART-like clustering is suggested as a natural feasible solution to the two problems of determining the number of clusters and clustering data. A 2D artificial data set is tested to demonstrate the performance of the proposed algorithm.