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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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Assigning class labels to k-means clusters

If you look at the names in your kmeans object you will notice that there is a "cluster" object. This contains the class labels ordered the same as your input data. Here is a simple example that binds …
Jeffrey Evans's user avatar