On Tue, Nov 23, 2010 at 02:47:10PM +0100, Sebastian Walter wrote: > Well, I don't know what the best method is to solve your problem, so > take the following with a grain of salt: > Wouldn't it be better to change the model than modifying the > optimization algorithm?
In this case, that's not possible. You can think of this parameter as the number of components in a PCA (it's actually a more complex dictionnary learning framework), so it's a parameter that is discrete, and I can't do anything about it :). > It sounds as if the resulting objective function is piecewise > constant. > AFAIK most optimization algorithms for continuous problems require at > least Lipschitz continuous functions to work ''acceptable well''. Not > sure if this is also true for Nelder-Mead. Yes correct. We do have a problem. I have a Nelder-Mead that seems to be working quite well on a few toy problems. Gaƫl _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion