I see, sorry for my ignorance. Even though I would prefer a different
solution it does make sense, if the boundaries are meaningful in all
variables. I am not so sure what you do if some variables don't have
"natural" boundaries.
On Tue, 08 Nov 2011 22:57:51 +0100, Luc Maisonobe (Commented) (JIRA)
<[email protected]> wrote:
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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:
------------------------------------
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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