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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446796 ]
Tyler Ward commented on MATH-157:
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Not bad. Looks like everything is in the right place, modulo a transpose or two
perhaps, but looks good. The eigenvector reductio
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446759 ]
Remi Arntzen commented on MATH-157:
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now I see your comments... sigh
> Add support for SVD.
>
>
> Key: MATH-157
>
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446426 ]
Tyler Ward commented on MATH-157:
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One more thing. I don't think you can just use the Q from the QR reduction
(slipped my mind earlier). Try it, you'll see that it
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446423 ]
Tyler Ward commented on MATH-157:
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Also, about testing. I've found that the best way to test this is just with
random matrices. If you can use, say, 10,000 random m
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446421 ]
Tyler Ward commented on MATH-157:
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I think I see the confusion. Take a look at my first comment here. You don't
want to invert (or find eigenvectors of) the origina
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446407 ]
Remi Arntzen commented on MATH-157:
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> You know you can invert that matrix (it's orthogonal, so just take the
> transpose), and you can
> also invert the S matrix
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12446155 ]
Tyler Ward commented on MATH-157:
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A few notes.
You don't have to compute the eigenvectors of both mTm and mmT, just do which
ever one is smaller. You know you ca
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http://issues.apache.org/jira/browse/MATH-157?page=comments#action_12431127 ]
Tyler Ward commented on MATH-157:
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Forgive me if this seems like condescension, you can find this in any decent
math book, and it is about one of the most well unde
