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Is there any relation between k-means and the maximum-likelihood estimate in unsupervised learning? Any references would be appreciates!

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  • $\begingroup$ What have you tried? Have you tried interpreting k-means as EM algorithm already? $\endgroup$
    – Has QUIT--Anony-Mousse
    Nov 9 '14 at 21:53
  • $\begingroup$ That was the idea.... I read about EM can be view as k-means generalization... But I can't find any proof. Can anyone help me? $\endgroup$
    – Kevin
    Nov 10 '14 at 17:07
  • $\begingroup$ It's actually rather straightforward... first, have a look at e.g. Mclust in R, which is the R implementation of EM, and understand the model parameter; in particular the E model. $\endgroup$
    – Has QUIT--Anony-Mousse
    Nov 10 '14 at 18:31
  • $\begingroup$ Could you be more specific? Thank you so much! $\endgroup$
    – Kevin
    Nov 10 '14 at 21:20
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    $\begingroup$ No fun when you are in a hurry :D $\endgroup$
    – Kevin
    Nov 12 '14 at 1:44
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You can think as K-Means as EM Algorithm (With Hard Thresholding) for GMM.
Since EM is a method for Maximum Likelihood Estimation you have a connection.

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