Data clustering using hybrid improved cuckoo search method

Abstract

Data clustering is one of the prominent fields of data mining which detects natural groups in a dataset. For the high dimensional dataset, traditional methods generally do not perform efficiently to cluster the data. Therefore, this paper proposes a novel metaheuristic method for data clustering based on k-means and improved cuckoo search to extend the capabilities of traditional clustering methods. The effectiveness of proposed method is tested on the three microarray datasets. Experimen­tal results validate that the proposed method outperforms the existing methods.