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https://issues.apache.org/jira/browse/MATH-867?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Frank Hess updated MATH-867:
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Attachment: MATH867_patch
Attached a patch. It makes encode/decode identities and removes the
restrictions on infinite ranges. The test on fit resolution near upper/lower
bounds fails. I believe the reason is that defaulting sigma to 0.3 times the
range causes the fitter to jump from the initial value (which is order of 1
away from the target) to some huge value on the order of 1e16 on the first
step. The fitter then has to work its way all the way back to the target. It
doesn't reach the target exactly due to one of the many stop conditions
hard-coded into the generationLoop which decide that the fit is "good enough"
and quit. That should probably be entered as a different ticket though, in
that there is no way to override the internal stop conditions and make the
fitter try harder. The ConvergenceChecker which can be passed into the
optimizer only has the ability to terminate the optimizer earlier than it
normally would quit, it doesn't suppress the other stop conditions which can't
be directly controlled by the user.
> 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: MATH867_patch, 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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