K-medoids Crazy Firefly Algorithm For Unsupervised Data Clustering

Data clustering is an unsupervised process in which identical data are collected in groups. A clustering algorithm divides a set of objects into different subsets, these subsets are non-overlapping in nature, and each subset is considered as a cluster. In this paper, a modified clustering approach is developed on integration of k-medoids clustering algorithm with crazy firefly algorithm. The proposed algorithm is experimented on four different datasets. The main aim of the suggested algorithm is to give fast and accurate user specified clustering results from given datasets. Finally, the outcome obtained from the proposed algorithm is compared with both k-medoids clustering algorithm and k-medoids firefly clustering algorithm. The results of the suggested algorithm are better than the k-medoids algorithm and the k-medoids firefly clustering algorithm.