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https://issues.apache.org/jira/browse/MATH-867?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13467764#comment-13467764
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Nikolaus Hansen commented on MATH-867:
--------------------------------------
{quote}
And I have no idea how to improve the documentation...
{quote}
Here are my suggestions: Replace (several times)
{code}
* @param inputSigma Initial search volume; sigma of offspring objective
variables.
{code}
with
{code}
* @param inputSigma Initial standard deviations to sample new points from
startPoint
{code}
and
{code}
/**
* Individual sigma values - initial search volume. inputSigma determines
* the initial coordinate wise standard deviations for the search. Setting
* SIGMA one third of the initial search region is appropriate.
*/
{code}
with
{code}
/**
* Values in inputSigma define the initial coordinate-wise
* standard deviations for sampling new search points about
* startPoint.
* Setting inputSigma roughly to the predicted distance of
* startPoint to the actually desired optimum is appropriate.
* Small values for inputSigma induce the search to be more local
* and very small values are more likely to find a local optimum
* close to startPoint.
* Extremely small values will however lead to early termination.
*/
{code}
> 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
> Fix For: 3.1
>
> 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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