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 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 -- This message is automatically generated by JIRA. - You can reply to this email to add a comment to the issue online.