An Alternative Technique of Selecting the Initial Cluster Centers in the k-means Algorithm for Better Clustering

Abstract

Although k-means works well in many cases it offers no accuracy guarantee and it has no idea to select ideal cluster representatives. This article presents a technique in which the initial cluster representatives in the standard k-means algorithm are chosen intelligently. Comparison of the quality of the clusters produced by the standard k-means algorithm… (More)

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