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From "Frank Hess (JIRA)" <>
Subject [jira] [Commented] (MATH-867) CMAESOptimizer with bounds fits finely near lower bound and coarsely near upper bound.
Date Mon, 24 Sep 2012 13:28:07 GMT


Frank Hess commented on MATH-867:

I've sent an email to the original author.  I've copied what I wrote to him below for reference:

I was wondering if you have any input on this bug in the Apache Commons implementation of
your algorithm:

It seems to be due to their attempt to follow your "encoding of variables" hint.  They map
parameters on to the interval [0,1] when boundaries are provided, which can have a bad interaction
with how floating point variable ULP are distributed.  Since your hint seems to suggest the
main point of this encoding is just make the width of the intervals uniform, it seems to me
they could just scale the boundaries onto a interval of unit width without offseting the interval
to start at zero.  This would get rid of the mismatch in ULP distribution between the scaled
interval and the original boundaries.

> CMAESOptimizer with bounds fits finely near lower bound and coarsely near upper bound.

> ---------------------------------------------------------------------------------------
>                 Key: MATH-867
>                 URL:
>             Project: Commons Math
>          Issue Type: Bug
>            Reporter: Frank Hess
>         Attachments:
> 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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