eigenvalues in LDA

hello, the problem I'm dealing with is finding eigenvalues and
eigenvectors of a
real, non-simmetric matrix, to perform Linear Discrminant Analysis of
data.
I know it is possible to find them by reducing the matrix to
Hessenberg form ("Numerical recipes in C").
But now I'm facing the problem of selecting the largest eigenvalues
(that's what LDA theory says): as they can be complex, should I choose
the largest modules?
Thanks to anyboddy can help me
geordie

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