[SciPy-User] fmin_cg fmin_bfgs "Desired error not necessarily achieveddue to precision loss"

[Dan Stowell]

(Bump)

Anyone got any suggestions about this "precision loss" issue, please?

I found this message from last year, suggesting that using dot instead 
of sum might help (yuck):
http://comments.gmane.org/gmane.comp.python.numeric.general/41268

- but no difference here, I still get the optimisation stopping after 
three iterations with that complaint.

Any tips welcome

Thanks
Dan



On 19/11/11 19:19, Dan Stowell wrote:
> Hi,
>
> I'm translating a fairly straightforward optimisation code example from
> octave. (Attached - it does a quadratic regression, with a tweaked
> regularisation function.)
>
> Both fmin_cg and fmin_bfgs give me poor convergence and this warning:
>
> "Desired error not necessarily achieveddue to precision loss"
>
> This is with various regularisation strengths, with normalised data, and
> with high-precision data (float128).
>
> Is there something I can do to enable these to converge properly?
>
> Thanks
> Dan
>
> (Using ubuntu 11.04, python 2.7.1, scipy 0.8)
>

-- 
Dan Stowell
Postdoctoral Research Assistant
Centre for Digital Music
Queen Mary, University of London
Mile End Road, London E1 4NS
http://www.elec.qmul.ac.uk/digitalmusic/people/dans.htm
http://www.mcld.co.uk/