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From "Luc Maisonobe (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (MATH-924) new multivariate vector optimizers cannot be used with large number of weights
Date Fri, 28 Dec 2012 20:20:12 GMT

     [ https://issues.apache.org/jira/browse/MATH-924?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Luc Maisonobe resolved MATH-924.
--------------------------------

       Resolution: Fixed
    Fix Version/s: 3.1.1

Fixed in subversion repository as of r1426616.
                
> new multivariate vector optimizers cannot be used with large number of weights
> ------------------------------------------------------------------------------
>
>                 Key: MATH-924
>                 URL: https://issues.apache.org/jira/browse/MATH-924
>             Project: Commons Math
>          Issue Type: Bug
>            Reporter: Luc Maisonobe
>            Priority: Critical
>             Fix For: 3.1.1
>
>
> When using the Weigth class to pass a large number of weights to multivariate vector
optimizers, an nxn full matrix is created (and copied) when a n elements vector is used. This
exhausts memory when n is large.
> This happens for example when using curve fitters (even simple curve fitters like polynomial
ones for low degree) with large number of points. I encountered this with curve fitting on
41200 points, which created a matrix with 1.7 billion elements.

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