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arXiv · 1705.03613

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

Hassan Ismkhan
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Abstract

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). This paper proposed a method for initialization of the k-means using the concept of useful nearest center for each data point.

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Hassan Ismkhan. 2017-05-10. An initialization method for the k-means using the concept of useful nearest centers. https://arxiv.org/abs/1705.03613

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