Github user jkbradley commented on the pull request:
https://github.com/apache/spark/pull/3022#issuecomment-68312524
@tgaloppo Thanks for the updates, and thanks for all of your work in
getting this ready!
LGTM
CC: @mengxr
After this is merged, I'll make some JIRAs for the various item we've
discussed along the way + a few more. Let me know if I've missed anything here:
* Add parameters: seed, maxIterations
* Use sparse vectors more efficiently
* If numFeatures or k are large, distribute matrix inverses for Gaussian
initialization.
* Breeze pinv fails when the matrix is singular:
[https://github.com/scalanlp/breeze/issues/304] Do SVD instead.
* Make MultivariateGaussian public, and update GMM API
* Check for NaNs:
* in computeSoftAssignments (if all pdfs = 0)
* in values when constructing a GMM
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