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https://issues.apache.org/jira/browse/SPARK-5021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14305605#comment-14305605
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Manoj Kumar commented on SPARK-5021:
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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: https://issues.apache.org/jira/browse/SPARK-5021
> 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 dimensions.
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