Wed May 20 15:51:26 CDT 2009
Makes sense. Thanks!
On Wed, May 20, 2009 at 4:48 PM, David Warde-Farley <email@example.com>wrote:
> On 20-May-09, at 3:51 PM, Jason Rennie wrote:
> > Hello,
> > I'm planning to use this function to optimize a least squares
> > objective. I
> > noticed that the "norm" argument defaults to "inf" or max norm.
> > Does this
> > mean that (by default) the search is done in max-norm space rather
> > than
> > L2/Euclidean norm space? Should I be worried about this setting?
> No; the termination criterion is based on the norm of the gradient. By
> default, it uses the infinity norm.
> This simply means that by default, the search terminates when _every_
> element of the returned gradient is less than gtol. This is a bit
> easier to think about than figuring out a tolerance on the 2-norm of
> the gradient vector, especially in very high dimensional spaces.
> SciPy-user mailing list
Research Scientist, ITA Software
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