On Feb 26, 2014, at 6:23 PM, Bruce A Johnson <johnsonb@umbc.edu> wrote:
> The NonLinearConjugateGradientOptimizer does a line search for a zero in the gradient
(see comment from source below), rather than a search for a minimum of the function (the latter
is what is used in Numerical Recipes and in the simple discussion on Wikipedia ( http://en.wikipedia.org/wiki/Nonlinear_conjugate_gradient_method).
Is this wise? It seems a clever idea, but in a complicated surface with numerical errors
the zero in the gradient may not be at a function minimum and the algorithm could be a deoptimizer.
I ask because (in a problem too complex too easily reproduce) I'm sometimes getting junk
as output of this routine.
>
> Bruce
>
> Comment for the LIneSearchFunction
>
> 350 * The function represented by this class is the dot product of
> 351 * the objective function gradient and the search direction. Its
> 352 * value is zero when the gradient is orthogonal to the search
> 353 * direction, i.e. when the objective function value is a local
> 354 * extremum along the search direction.
Just realized, in reviewing all open bugs, that this has already been reported as Math1092
( https://issues.apache.org/jira/browse/MATH1092 )
I agree with the assignment priority, this is a Major bug.
Bruce

To unsubscribe, email: devunsubscribe@commons.apache.org
For additional commands, email: devhelp@commons.apache.org
