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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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Is K-Means used the right way?
I have this model where I have a count of a word. Every day I do a count of the word and then calculate a simple ratio for this word by saying:
Ratio = Current day count / Past day count
So I now h …