This paper presents a method for enhancing the performance of current clustering algorithms; the method is based on Particle Swarm Optimization techniques. Namely, a preprocessing step aims at bringing rdquocloserrdquo objects which are likely to belong to the same cluster, while increasing the distance between objects likely to belong to different clusters. Experimental results show significantly improved performance for further clustering procedures especially when non-spherical clusters are involved.
This article is authored also by Synbrain data scientists and collaborators. READ THE FULL ARTICLE