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From "Frank Hess (JIRA)" <j...@apache.org>
Subject [jira] [Comment Edited] (MATH-867) CMAESOptimizer with bounds fits finely near lower bound and coarsely near upper bound.
Date Mon, 24 Sep 2012 16:11:08 GMT

    [ https://issues.apache.org/jira/browse/MATH-867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13461878#comment-13461878
] 

Frank Hess edited comment on MATH-867 at 9/25/12 3:09 AM:
----------------------------------------------------------

To elaborate on my previous point, the CMAESOptimizer also doesn't allow mixing of bounded
and unbounded parameters.  So, if I only want to apply a bound to one parameter of a multi-parameter
fit, then the best I can do is set the bounds of the "unbounded" parameters to be [-VeryLargeValue,
+VeryLargeValue].  This causes the fit precision around zero for the "unbounded" parameters
to be much worse than when no bounds are specified at all.
                
      was (Author: fhess):
    To elaborate on my previous point, the CMAESOptimizer also doesn't allow mixing of bounded
and unbounded parameters.  So, if I only want to apply a bound to one parameter of a multi-parameter
fit, then the best I can do is set the bounds of the "unbounded" parameters to be [-VeryLargeValue,
+VeryLargeValue].  This causes the fit precision around zero for the "unbounded" to be much
worse than when no bounds are specified at all.
                  
> CMAESOptimizer with bounds fits finely near lower bound and coarsely near upper bound.

> ---------------------------------------------------------------------------------------
>
>                 Key: MATH-867
>                 URL: https://issues.apache.org/jira/browse/MATH-867
>             Project: Commons Math
>          Issue Type: Bug
>            Reporter: Frank Hess
>         Attachments: Math867Test.java
>
>
> When fitting with bounds, the CMAESOptimizer fits finely near the lower bound and coarsely
near the upper bound.  This is because it internally maps the fitted parameter range into
the interval [0,1].  The unit of least precision (ulp) between floating point numbers is much
smaller near zero than near one.  Thus, fits have much better resolution near the lower bound
(which is mapped to zero) than the upper bound (which is mapped to one).  I will attach a
example program to demonstrate.

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