You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@mahout.apache.org by dl...@apache.org on 2014/03/10 06:01:27 UTC
svn commit: r1575825 -
/mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext
Author: dlyubimov
Date: Mon Mar 10 05:01:27 2014
New Revision: 1575825
URL: http://svn.apache.org/r1575825
Log:
CMS commit to mahout by dlyubimov
Modified:
mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext
Modified: mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext
URL: http://svn.apache.org/viewvc/mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext?rev=1575825&r1=1575824&r2=1575825&view=diff
==============================================================================
--- mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext (original)
+++ mahout/site/mahout_cms/trunk/content/users/dim-reduction/ssvd.mdtext Mon Mar 10 05:01:27 2014
@@ -89,14 +89,13 @@ Note: numerical stability of R algorithm
#### Modified SSVD Algorithm. ####
-<pre>
-Given an \(m\times n\)
-matrix \(\mathbb{A}\), a target rank \\(k\in\mathbb{N}\_{1}\)
-, an oversampling parameter \(p\in\mathbb{N}_{1}\),
-and the number of additional power iterations \(q\in\mathbb{N}_{0}\),
-this procedure computes an \(m\times\left(k+p\right)\)
-SVD \(\mathbf{A\approx U}\boldsymbol{\Sigma}\mathbf{V}^{\top}\):
-</pre>
+
+Given an $m\times n$
+ matrix A, a target rank $k\in\mathbb{N}_{1}$
+ , an oversampling parameter $p\in\mathbb{N}_{1}$
+ , and the number of additional power iterations $q\in\mathbb{N}_{0}$
+ , this procedure computes an $m\times\left(k+p\right)$
+ SVD $\mathbf{A\approx U}\boldsymbol{\Sigma}\mathbf{V}^{\top}$
<script type="text/javascript"