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From "Mick (JIRA)" <j...@apache.org>
Subject [jira] Created: (MATH-177) Provide a general minimizing package with a classical Gauss-Newton algorithm
Date Wed, 16 Jan 2008 21:03:34 GMT
Provide a general minimizing package with a classical Gauss-Newton algorithm
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                 Key: MATH-177
                 URL: https://issues.apache.org/jira/browse/MATH-177
             Project: Commons Math
          Issue Type: Improvement
    Affects Versions: 2.0
            Reporter: Mick
             Fix For: 2.0


Currently the math API provides least squares only method for minimizing (solving). The limitation
to least-squares problems comes from the Levenberg-Marquardt algorithm. A more general minimizer
(not for quadratic forms) could be implemented by refactoring this with a classical GN, steepest
descent and also conjugate gradient. We could use them as a basis for some least-squares solvers
(and also keep the very efficient and specialized Levenberg-Marquardt too).

Based on email exchange with Luc Maisonobe entitled [math] Minimizer on 1/15/08.


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