Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/9736#discussion_r45122717
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
---
@@ -379,25 +379,43 @@ class RowMatrix @Since("1.0.0") (
* Note that this cannot be computed on matrices with more than 65535
columns.
*
* @param k number of top principal components.
- * @return a matrix of size n-by-k, whose columns are principal
components
+ * @return a matrix of size n-by-k, whose columns are principal
components, and
+ * a vector of values which indicate how much variance each principal
component
--- End diff --
It is not very clear from the doc whether we return the absolute variance
explained or the proportions. How about `a vector of proportions of variance
explained by each principal component` and change the method name to
`computePrincipalComponentsAndExplainedVariance`?
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