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https://issues.apache.org/jira/browse/MATH-702?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13146597#comment-13146597
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Luc Maisonobe commented on MATH-702:
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Does "coordinate-wise" means that each coordinate has its dedicated sigma ?
If so, this is what I have set up. The sigma vector was already an array with
the same dimension as both the state vector and the lower/upper bounds, so I
have simply used upper[i] - lower[i] as a multiplication factor for sigma[i].
Does what I did make sense ?
> CMA-ES optimizer input sigma should not be normalized by user
> -------------------------------------------------------------
>
> Key: MATH-702
> URL: https://issues.apache.org/jira/browse/MATH-702
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 3.0
> Reporter: Luc Maisonobe
> Priority: Minor
> Fix For: 3.0
>
>
> I am trying to use CMA-ES optimizer with simple boundaries.
> It seems the inputSigma parameter should be normalized as it is checked
> against the [0 - 1] range in the checkParameters private method and as its
> value defaults to 0.3 if not not set in the initializeCMA private method.
> I would have expected this value to be in the same units as the user
> parameters and to be normalized as part of an internal processing step
> instead of relying to the user doing this. I think the method need normalized
> values internally, as per the encode/decode methods in the inner class
> FitnessFunction suggest.
> The optimizer should accept values in the same units as the other parameters
> and use "encode" (or a similar function) to do the normalization. This way,
> normalization is considered an internal implementation detail.
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