A tutorial on Particle Swarm Optimization Clustering
This is an incremental tutorial aimed at researchers or practitioners interested in applying Particle Swarm Optimization to clustering tasks.
This paper provides a tutorial on using Particle Swarm Optimization for data clustering, including an in-depth analysis, Matlab implementation, and a comparison showing that it achieves competitive results against the K-Means approach.
This paper proposes a tutorial on the Data Clustering technique using the Particle Swarm Optimization approach. Following the work proposed by Merwe et al. here we present an in-deep analysis of the algorithm together with a Matlab implementation and a short tutorial that explains how to modify the proposed implementation and the effect of the parameters of the original algorithm. Moreover, we provide a comparison against the results obtained using the well known K-Means approach. All the source code presented in this paper is publicly available under the GPL-v2 license.