Github user mengxr commented on the pull request:
https://github.com/apache/spark/pull/2070#issuecomment-53217715
I've merged this into master and branch-1.1. Thanks!!
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Github user asfgit closed the pull request at:
https://github.com/apache/spark/pull/2070
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Github user SparkQA commented on the pull request:
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Github user atalwalkar commented on the pull request:
https://github.com/apache/spark/pull/2070#issuecomment-53130497
Aside from the one issue of $U$ being the left singular vectors, this looks
good to me.
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Github user SparkQA commented on the pull request:
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Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/2070#discussion_r16523887
--- Diff: docs/mllib-dimensionality-reduction.md ---
@@ -119,14 +137,13 @@ statistical method to find a rotation such that the
first coordinate has the lar
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Github user atalwalkar commented on a diff in the pull request:
https://github.com/apache/spark/pull/2070#discussion_r16514920
--- Diff: docs/mllib-dimensionality-reduction.md ---
@@ -11,7 +11,7 @@ displayTitle: MLlib -
Dimensionality Reduction
of reducing the number of variab
Github user atalwalkar commented on a diff in the pull request:
https://github.com/apache/spark/pull/2070#discussion_r16514855
--- Diff: docs/mllib-dimensionality-reduction.md ---
@@ -11,7 +11,7 @@ displayTitle: MLlib -
Dimensionality Reduction
of reducing the number of variab
GitHub user rezazadeh opened a pull request:
https://github.com/apache/spark/pull/2070
[MLlib][SPARK-2997] Update SVD documentation to reflect roughly square
Update the documentation to reflect the fact we can handle roughly square
matrices.
You can merge this pull request into a G
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