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https://issues.apache.org/jira/browse/MAHOUT-1464?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14031707#comment-14031707
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ASF GitHub Bot commented on MAHOUT-1464:
----------------------------------------
Github user pferrel commented on a diff in the pull request:
https://github.com/apache/mahout/pull/18#discussion_r13782871
--- Diff:
math-scala/src/main/scala/org/apache/mahout/math/scalabindings/MatrixOps.scala
---
@@ -188,8 +188,8 @@ object MatrixOps {
def apply(f: Vector): Double = f.sum
}
- private def vectorCountFunc = new VectorFunction {
- def apply(f: Vector): Double = f.aggregate(Functions.PLUS,
Functions.greater(0))
+ private def vectorCountNonZeroElementsFunc = new VectorFunction {
+ def apply(f: Vector): Double = f.aggregate(Functions.PLUS,
Functions.notEqual(0))
--- End diff --
used Sebastian's getNumNonZeroElements here. Is your issue with Dmitriy's
suggestion? This is only for in core matrices, the code used for drms is the
stuff in SparkEngine, which accumulates using the nonZero iterator on row
Vectors.
> Cooccurrence Analysis on Spark
> ------------------------------
>
> Key: MAHOUT-1464
> URL: https://issues.apache.org/jira/browse/MAHOUT-1464
> Project: Mahout
> Issue Type: Improvement
> Components: Collaborative Filtering
> Environment: hadoop, spark
> Reporter: Pat Ferrel
> Assignee: Pat Ferrel
> Fix For: 1.0
>
> Attachments: MAHOUT-1464.patch, MAHOUT-1464.patch, MAHOUT-1464.patch,
> MAHOUT-1464.patch, MAHOUT-1464.patch, MAHOUT-1464.patch, run-spark-xrsj.sh
>
>
> Create a version of Cooccurrence Analysis (RowSimilarityJob with LLR) that
> runs on Spark. This should be compatible with Mahout Spark DRM DSL so a DRM
> can be used as input.
> Ideally this would extend to cover MAHOUT-1422. This cross-cooccurrence has
> several applications including cross-action recommendations.
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