An hybrid approach for data clustering using k-means and Teaching Learning Based Optimization

Abstract

A new efficient method for optimization, ‘Teaching-Learning Based Optimization (TLBO)’, has been proposed very recently for addressing the mechanical design problems and it can also be used for clustering numerical data. In this paper teaching learning based optimization is used along with kmeans algorithm for clustering the data into user specified number of clusters. It shows how TLBO can be used to find the centroids of a user specified number of clusters. The hybrid algorithm has been implemented for attaining better results for clustering.