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authorGravatar Jitse Niesen <jitse@maths.leeds.ac.uk>2013-08-06 08:03:39 +0100
committerGravatar Jitse Niesen <jitse@maths.leeds.ac.uk>2013-08-06 08:03:39 +0100
commit2f0faf117ead5f92424bd3c67c434eb3ecaa9661 (patch)
tree0679a52b8cc02aeb0fc1a02457e9037287adf840 /doc
parent8710440951860e7dbf4382916244e5fed498d756 (diff)
Remove LinearLeastSquares.dox , which should not have been added.
Accidentally included in changeset e37ff98bbb21f2ee44c6d912002ddf2cdf05ccda .
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-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".
-
-*/
-
-}