Rank: 1064 based on 80 downloads (last 30 days) and 1 file submitted
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R. Bunschoten

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Univ van Amsterdam

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03 Nov 1999 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten dist, euclidean, distance, neural networks, fuzzy logic, l2 80 23
  • 4.61111
4.6 | 18 ratings
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19 Apr 2012 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten Chithanar, Arun Kumar

Thanks. This saved me time!
21 Sep 2011 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten vince

I find a simple

sqrt((a-b)'*(a-b))

faster to compute the Euclidean distance
30 Aug 2011 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten Torabi, Ali Asghar

Thanks. using repmat has made it useful and fast.
26 Feb 2011 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten Tacchetti, Andrea

Things can go wrong in extreme cases.
If dimensionality is very high numerical errors will kick in.

I have twenty-five hundred 10'000 dimensional vectors stored in matrix X and

~
sum(diag(distance(X',X'))) = 6e-4;
~

Other than that, great job!
11 Jan 2011 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten R., T.

Top Tags Applied by R.
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dist, distance, euclidean, fuzzy logic, neural networks
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Updated   File Tags Downloads
(last 30 days) 		Comments Rating
03 Nov 1999 distance.m A fully vectorized function that computes the Euclidean distance matrix between two sets of vectors. Author: R. Bunschoten dist, euclidean, distance, neural networks, fuzzy logic, l2 80 23
  • 4.61111
4.6 | 18 ratings

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