I was fitting GMM clusters with diagonal covariance on my data using EM with $n$
(=5e6) points, each having $m$
(=160) dimensions. I wanted to get around $k$
(=400) clusters. But this is taking a lot of time.
My question are:
- What is the per iteration complexity of GMM EM given $n$, $m$ and $k$?
- Which parameters might help me the most in reducing the runtime most while giving useful clusters?
- Also what is the suggested number of iterations required for EM to converge given this metadata? I'm currently working iterating 100 times.
- How is this affected by going from diagonal covariance to other covariances(tied covariance or full covariance)?