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https://issues.apache.org/jira/browse/FLINK-1737?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14909813#comment-14909813
]
ASF GitHub Bot commented on FLINK-1737:
---------------------------------------
Github user daniel-pape commented on a diff in the pull request:
https://github.com/apache/flink/pull/1078#discussion_r40507074
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/math/SparseVector.scala
---
@@ -85,6 +85,34 @@ case class SparseVector(
}
}
+ /** Returns the outer product (a.k.a. Kronecker product) of `this`
+ * with `other`. The result is given in
[[org.apache.flink.ml.math.SparseMatrix]]
+ * representation.
+ *
+ * @param other a Vector
+ * @return the [[org.apache.flink.ml.math.SparseMatrix]] which equals
the outer product of `this`
+ * with `other.`
+ */
+ override def outer(other: Vector): SparseMatrix = {
+ val numRows = size
+ val numCols = other.size
+
+ val otherIndices = other match {
+ case sv @ SparseVector(_, _, _) => sv.indices
+ case dv @ DenseVector(_) => (0 until dv.size).toArray
+ }
+
+ val entries = for {
+ i <- indices
+ j <- otherIndices
+ value = this(i) * other(j)
--- End diff --
Thanks for pointing this out.
> Add statistical whitening transformation to machine learning library
> --------------------------------------------------------------------
>
> Key: FLINK-1737
> URL: https://issues.apache.org/jira/browse/FLINK-1737
> Project: Flink
> Issue Type: New Feature
> Components: Machine Learning Library
> Reporter: Till Rohrmann
> Assignee: Daniel Pape
> Labels: ML, Starter
>
> The statistical whitening transformation [1] is a preprocessing step for
> different ML algorithms. It decorrelates the individual dimensions and sets
> its variance to 1.
> Statistical whitening should be implemented as a {{Transfomer}}.
> Resources:
> [1] [http://en.wikipedia.org/wiki/Whitening_transformation]
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