MBA-IF:A New Data Clustering Method Using Modified Bat Algorithm and Levy Flight

Data clustering plays an important role in partitioning the large set of data objects into known/unknown number of groups or clusters so that the objects in each cluster are having high degree of similarity while objects in different clusters are dissimilar to each other. Recently a number of data clustering methods are explored by using traditional methods as well as nature inspired swarm intelligence algorithms. In this paper, a new data clustering method using modified bat algorithm is presented. The experimental results show that the proposed algorithm is suitable for data clustering in an efficient and robust way.