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Clustering is an essential task in Data Mining process which is used for the purpose to make groups or clusters of the given data set based on the similarity between them. K-Means clustering is a clustering method in which the given data set is divided into K number of clusters. This paper is intended to give the introduction about K-means clustering and its algorithm. The experimental results of K-means clustering and its performance in case of execution time is discussed here. But there are certain limitations in K-means clustering algorithm such as it takes more time for execution.
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