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https://issues.apache.org/jira/browse/MATH-342?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Dimitri Pourbaix resolved MATH-342.
-----------------------------------
Resolution: Fixed
Fix Version/s: Nightly Builds
The two identified troublesome behaviors of EigenDecomposition are corrected.
Besides the regular unit tests, the two classes SingularValueDecompositionimpl
and EigenDecompositionImpl have now been successfully tested over 300k+ systems
coming from some astronomical application. No crash reported!
> SVD crashes when applied to a strongly rectangular matrix (typical case of
> least-squares problem)
> -------------------------------------------------------------------------------------------------
>
> Key: MATH-342
> URL: https://issues.apache.org/jira/browse/MATH-342
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: Nightly Builds
> Reporter: Dimitri Pourbaix
> Assignee: Dimitri Pourbaix
> Fix For: Nightly Builds
>
>
> When SVD is applied to a strongly rectangular matrix (number of rows way
> larger than number of columns, typical case of least-squares problem), finite
> precision arithmetics shows up:
> - in EigenDecompositionImpl.isSymmetric: a by-definition symmetric matrix
> returns false;
> - in EigenDecompositionImpl.findEigenVectors: too many iterations exception
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