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From "Manoj Kumar (JIRA)" <>
Subject [jira] [Commented] (SPARK-5021) GaussianMixtureEM should be faster for SparseVector input
Date Wed, 04 Feb 2015 17:52:34 GMT


Manoj Kumar commented on SPARK-5021:

Thanks for the comment. That also seems to fail, since I use properties like index, and valueAt
which are exclusive to BSV.
: error: value index is not a member of breeze.linalg.Vector[Double]

How about method overloading?

   // Dense Case
  def vectorMean(x: IndexedSeq[BDV[Double]]): BDV[Double] = {

   // Sparse Case
   def vectorMean(x: IndexedSeq[BSV[Double]]): BDV[Double] = {

> GaussianMixtureEM should be faster for SparseVector input
> ---------------------------------------------------------
>                 Key: SPARK-5021
>                 URL:
>             Project: Spark
>          Issue Type: Improvement
>          Components: MLlib
>    Affects Versions: 1.3.0
>            Reporter: Joseph K. Bradley
>            Assignee: Manoj Kumar
> GaussianMixtureEM currently converts everything to dense vectors.  It would be nice if
it were faster for SparseVectors (running in time linear in the number of non-zero values).
> However, this may not be too important since clustering should rarely be done in high

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