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k-means is a method to partition data into clusters by finding a specified number of means, k, s.t. when data are assigned to clusters w/ the nearest mean, the w/i cluster sum of squares is minimized

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k-means for set of integers

In R, you could do something like this: > kmeans(c(11, 22, 3, 12, 1, 23, 21, 13, 2), c(1, 2, 3)) K-means clustering with 3 clusters of sizes 1, 2, 6 Cluster means: [,1] 1 1.0 2 2.5 3 17.0 Clust …
Alex Woolford's user avatar