Hierarchical growing cell structures: TreeGCS

We propose a hierarchical, unsupervised clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS) neural network of Fritzke. Our algorithm improves an inconsistency in the GCS algorithm, where the network topology is susceptible to the ordering of the input vectors. We demonstrate improved stability of the GCS foundation by alternating the input vector order on each presentation. We evaluate our automatically produced cluster hierarchy against that generated by an ascendant hierarchical clustering dendogram. We use a small dataset to illustrate how our approach emulates the hierarchical clustering of the dendogram, regardless of the input vector order.

• Type: Conference
• Year: 2000
• Where: KES
• Authors: Victoria J. Hodge, James Austin
• Keywords: Hierarchical Clustering, Information Management, Input Vector, Input Vector Order, KES 2000