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https://issues.apache.org/jira/browse/MATH-867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13461878#comment-13461878
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Frank Hess edited comment on MATH-867 at 9/25/12 3:09 AM:
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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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