International Journal of Computer Applications
In data mining, agglomerative clustering algorithms are widely used because their flexibility and conceptual simplicity. However, their main drawback is their slowness. In this paper, a simple agglomerative clustering algorithm with a low computational complexity, is proposed. This method is especially convenient for performing clustering on large data sets, and could also be used as a linear time initialization method for other clustering algorithms, like the commonly used k-means algorithm. Experiments conducted on some standard data sets confirm that the proposed approach is effective.