> From: Ferdinando Ametrano [mailto:
[hidden email]]
<snip>
> Why your constrained algorithm seems to perform poorly in the
unconstrained
> case? I know I'm probably missing some key point here, and would love
to be
> enlightened.
>
Should have replied to this message...
Intuitively, you can see why as the final measure is likely to be a
biased number as it has to fit into the initial choices. A simple way
of improving the randomness is to shuffle the tuple, i.e. randomly
select the axes to constrain, before allocating the weights. That way
the bias is randomly distributed and hopefully a little nicer.
Regards,
Matt Hurd.
_________________
Matt Hurd
+61.2.8226.5029
[hidden email]
Susquehanna
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