SVD crashes when applied to a strongly rectangular matrix (typical case of
least-squares problem)
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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
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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