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The goal of clustering is to divide the data set in predetermined ("K") number of clusters around the average locations ("means"), so the algorithm is also known as the K-Means algorithm. Like other techniques it is applied mostly on people, to discover hidden grouping that can't be noticed at the first glimpse.
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