Hi, Can someone please explain that if the EM algorithm is initialised with K-means, then one needs to compute complete-data maximum likelihood estimation (MLE) or maximum a posteriori (MAP)?
In my understanding, setting the priors leads the EM algorithm to maximising MAP problem. So, by initialising using K-means, we are setting priors.
Thank you.
Dear Rabia,
Please read the attached Thesis with the title "Initializing the EM Algorithm for Data Clustering and Sub-population Detection". I hope this will help you out.
Good luck
Thank you Firdos for sharing the article. I have read this and yes, they calculated MLE and not MAP.
But, in other work (Model-Based Clustering and Visualization of Navigation Patterns on a Web Site by Igor V. Cadez et al.) when priors are set using Dirichlet distribution, MAP is computed.
So, my concern is why MAP is not computed in case of K-means priors?
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