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author | Jitse Niesen <jitse@maths.leeds.ac.uk> | 2013-08-06 08:03:39 +0100 |
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committer | Jitse Niesen <jitse@maths.leeds.ac.uk> | 2013-08-06 08:03:39 +0100 |
commit | 2f0faf117ead5f92424bd3c67c434eb3ecaa9661 (patch) | |
tree | 0679a52b8cc02aeb0fc1a02457e9037287adf840 /doc | |
parent | 8710440951860e7dbf4382916244e5fed498d756 (diff) |
Remove LinearLeastSquares.dox , which should not have been added.
Accidentally included in changeset e37ff98bbb21f2ee44c6d912002ddf2cdf05ccda
.
Diffstat (limited to 'doc')
-rw-r--r-- | doc/LinearLeastSquares.dox | 27 |
1 files changed, 0 insertions, 27 deletions
diff --git a/doc/LinearLeastSquares.dox b/doc/LinearLeastSquares.dox deleted file mode 100644 index ab21a87ae..000000000 --- a/doc/LinearLeastSquares.dox +++ /dev/null @@ -1,27 +0,0 @@ -namespace Eigen { - -/** \eigenManualPage LinearLeastSquares Solving linear least squares problems - -lede - -\eigenAutoToc - -\section LinearLeastSquaresCopied Copied - -The best way to do least squares solving is with a SVD decomposition. Eigen provides one as the JacobiSVD class, and its solve() -is doing least-squares solving. - -Here is an example: -<table class="example"> -<tr><th>Example:</th><th>Output:</th></tr> -<tr> - <td>\include TutorialLinAlgSVDSolve.cpp </td> - <td>\verbinclude TutorialLinAlgSVDSolve.out </td> -</tr> -</table> - -For more information, including faster but less reliable methods, read our page concentrating on \ref LinearLeastSquares "linear least squares problems". - -*/ - -} |