In this paper we have investigated the performance of PSO Particle Swarm
Optimization based clustering on few real world data sets and one artificial
data set. The performances are measured by two metric namely quantization error
and inter-cluster distance. The K means clustering algorithm is first
implemented for all data sets, the results of which form the basis of
comparison of PSO based approaches. We have explored different variants of PSO
such as gbest, lbest ring, lbest vonneumann and Hybrid PSO for comparison
purposes.