Best Clustering Configuration Metrics: Towards Multiagent Based Clustering

Multi-Agent Clustering (MAC) requires a mechanism for identifying the most appropriate cluster configuration. This paper reports on experiments conducted with respect to a number of validation metrics to identify the most effective metric with respect to this context. This paper also describes a process whereby such metrics can be used to determine the optimum parameters typically required by clustering algorithms, and a process for incorporating this into a MAC framework to generate best cluster configurations with minimum input from end users.