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author | Reza Zadeh <rizlar@gmail.com> | 2014-01-01 20:03:47 -0800 |
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committer | Reza Zadeh <rizlar@gmail.com> | 2014-01-01 20:03:47 -0800 |
commit | 53ccf65362d935f89fb9e27b4a3485454fa4c882 (patch) | |
tree | d7a4fe0dba3e6a8316881edc2d8d3047bef04954 /docs | |
parent | 97dc527849b836703811acdbd6767685585099df (diff) | |
download | spark-53ccf65362d935f89fb9e27b4a3485454fa4c882.tar.gz spark-53ccf65362d935f89fb9e27b4a3485454fa4c882.tar.bz2 spark-53ccf65362d935f89fb9e27b4a3485454fa4c882.zip |
doc tweaks
Diffstat (limited to 'docs')
-rw-r--r-- | docs/mllib-guide.md | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index 8c490eba69..711187fbea 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -215,7 +215,7 @@ Available algorithms for gradient descent: # Singular Value Decomposition Singular Value Decomposition for Tall and Skinny matrices. -Given an *m x n* matrix *A*, this will compute matrices *U, S, V* such that +Given an *m x n* matrix *A*, we can compute matrices *U, S, V* such that *A = U * S * V^T* |