EM Gaussian clustering is different from k means in that you are optimizing a theoretical likelihood rather than simply calculating the distances between points. As such, starting positions do not matter (at least as far as I am aware). I have only used the mclust package for clustering so i don't know what min.n.iter does.

EM Gaussian clustering is different from k means in that you are optimizing a theoretical likelihood rather than simply calculating the distances between points. As such, starting positions do not matter so much (at least as far as I am aware). I have only used the mclust package for clustering so i don't know what min.n.iter does.