spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "Manoj Kumar (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-5021) GaussianMixtureEM should be faster for SparseVector input
Date Wed, 04 Feb 2015 17:52:34 GMT

    [ https://issues.apache.org/jira/browse/SPARK-5021?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14305605#comment-14305605
] 

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: 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.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org


Mime
View raw message