An Algorithm for Clustering Data Based on Rough Set Theory

A variety of cluster analysis techniques exist to group objects having similar characteristics. While there have been recent advances in algorithms for clustering data, some are unable to handle uncertainty in the clustering process while others have stability issues. This paper proposes a new algorithm for clustering data based on rough set theory, which has the ability to handle the uncertainty in the clustering process.