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Avoid problem using a custom distance function in ClusteringTree?

Carlos Muñoz, Wolfram|Alpha
Posted 9 years ago
POSTED BY: Carlos Muñoz
4 Replies
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That's because of this I think:

EuclideanDistance[1, 2]
HammingDistance[1, 2]

the first one gives a number, while the second doesn't... So in order to fix it you have to put data in a certain format:

ClusteringTree[{1, 2, 5}, DistanceFunction -> EuclideanDistance]
ClusteringTree[{{1}, {2}, {5}}, DistanceFunction -> HammingDistance]
POSTED BY: Sander Huisman

Last update:

I just realized I was using the wrong set of data, haha.

If it helps to explain, in case anyone has a similar problem, I was using sequences of different lengths when my custom function only worked with sequences of equal lengths.
POSTED BY: Carlos Muñoz 
Update:

The results I got were a bit odd, and I though it was because of my distance function, but when I checked my distance function with the data in a different format it gave me always a distance of 0.
POSTED BY: Carlos Muñoz

Thanks! My data was an association with strings as values, so I transformed them into lists with one element, as in your example, and it worked.
POSTED BY: Carlos Muñoz
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