[SciPy-user] scipy.optimize.fmin_cg

David Warde-Farley dwf@cs.toronto....
Wed May 20 15:48:47 CDT 2009

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.


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