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author | Reza Zadeh <rizlar@gmail.com> | 2014-01-01 20:01:13 -0800 |
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committer | Reza Zadeh <rizlar@gmail.com> | 2014-01-01 20:01:13 -0800 |
commit | b941b6f7b0131b4382b09740d56916574901fd55 (patch) | |
tree | 7dc50a2aad2f2ce3b4fa6d6c7c011786e24bf212 /docs/mllib-guide.md | |
parent | 185c882606112a49c1d7359cc1de00bd273c3050 (diff) | |
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doc tweaks
Diffstat (limited to 'docs/mllib-guide.md')
-rw-r--r-- | docs/mllib-guide.md | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/docs/mllib-guide.md b/docs/mllib-guide.md index 8c86369ae6..08d6d74853 100644 --- a/docs/mllib-guide.md +++ b/docs/mllib-guide.md @@ -231,12 +231,12 @@ Only singular vectors associated with singular values greater or equal to MIN_SVALUE are recovered. If there are k such values, then the dimensions of the return will be: -S is k x k and diagonal, holding the singular values on diagonal -U is m x k and satisfies U^T*U = eye(k) -V is n x k and satisfies V^TV = eye(k) +* *S* is *k x k* and diagonal, holding the singular values on diagonal. +* *U* is *m x k* and satisfies U^T*U = eye(k). +* *V* is *n x k* and satisfies V^TV = eye(k). All input and output is expected in sparse matrix format, 1-indexed -as tuples of the form ((i,j),value) all in RDDs +as tuples of the form ((i,j),value) all in RDDs. Below is example usage. {% highlight scala %} |