An Agglomerative Clustering Method for Large Data Sets
Omar Kettani, Faycal Ramdani, Benaissa Tadili · International Journal of Computer Applications · 2014
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.