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  1. Commons Math
  2. MATH-342

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

    Details

    • Type: Bug
    • Status: Closed
    • Priority: Major
    • Resolution: Fixed
    • Affects Version/s: 2.0
    • Fix Version/s: 2.1
    • Labels:
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      Description

      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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            • Assignee:
              dimpbx Dimitri Pourbaix
              Reporter:
              dimpbx Dimitri Pourbaix
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                Updated:
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