An initialization method for the k-means using the concept of useful nearest centers

10 May 2017Hassan Ismkhan

The aim of the k-means is to minimize squared sum of Euclidean distance from the mean (SSEDM) of each cluster. The k-means can effectively optimize this function, but it is too sensitive for initial centers (seeds)... (read more)

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