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So, getting an "idea" of the optimal number of clusters in k-means is well documented. I found an article on doing this in gaussian mixtures, but not sure I am convinced by it, don't understand it very well. Is there a ... gentler way of doing this? Greetings

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Could you cite the article, or at least outline the methodology it proposes? It's hard to come up with a "gentler" way of doing this if we don't know the baseline :) – jbowman Jul 16 '12 at 18:30
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Geoff McLachlan and others have written books on mixture distributions. I am sure these include approaches to determining the number of components in a mixture. You could probably look there. I agree with jbowman that relieving your confusion would best be achieved if you would indicate to us what it is that you are confused about. – Michael Chernick Jul 16 '12 at 19:05
The Estimating Optimal Number of Gaussian Mixtures Based on Incremental k-means for Speaker Identification.... Is its title, it's free to download. It basically increments the number of clusters by 1 until you see that two clusters become dependant between each other, something like that. Thank you! – JEquihua Jul 18 '12 at 20:18

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