Re:Measure distance in n dimensions with Pythagoras
by pixcavator on Tuesday November 06, 2007 @09:09AM
(#76581)
I've used the 1-norm, aka "Manhattan", distance (with weights of course) for visual image search. I think the 1-norm is always a better choice than the Euclidean distance unless there is some clear geometric context.
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Re:Measure distance in n dimensions with Pythagoras
by machine on Tuesday November 06, 2007 @03:09PM
(#76731)
The 1-norm tends to also be less sensitive to outliers, and in machine learning, 1-norm regularization leads to sparse solutions. The real reason 2-norm is popular is that it is easy to minimize (differentiable).