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I am working on a problem of unsupervised classification. The data samples are fairly random. Unfortunately, I don't have the luxury of specifying the number of clusters. I would like to use some criteria to automatically identify the number of clusters.

For example, assume there are distinctly 2 clusters in the data points and I use 3 clusters. Is there method to infer that 2 is the right number of clusters vs 3?

Sharanbr
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  • Search https://stats.stackexchange.com/search?q=k+means+count+validation. Some threads provide answers, such as https://stats.stackexchange.com/questions/140711. – whuber Aug 11 '18 at 20:02
  • If you "don't have the luxury of specifying the number of clusters" then how will you do k means cluster analysis at all? Have you looked into hierarchical methods? – Peter Flom Aug 12 '18 at 10:25

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