How many kinds of Distance Function can we use?

I was reading stuffs about pattern recognition. Recently I want to make a survey of methods to evaluate similarities of vectors. As far as I know, there are Euclidean distances, Mahalanobis distances and Cosine Distance. Can anyone present some more names or keywords to search?

Upvotes: 4

Answers (4)

George

Reputation: 3845

You can define your own distance metrics too, so I would say there can be A LOT of possible distance metrics. Now if those metrics are good or have any meaning is another story.

Upvotes: 2

kc2001

Reputation: 5247

Also mutual neighbor distance (MND), Minkowski metric, Hausdorff distance, conceptual similarity, normalized Google distance, KL divergence, Spearman’s rank correlation, and Lin similarity. (Not all of these are vector based.)

I highly recommend Pattern Classification by Duda, Hart, and Stork for further reading. It is extensively cited.

Upvotes: 4

mitch

Reputation: 282

Pearson, Manhatten, Gower, Jaccard, Tanimoto, Russel Rao, Dice, Kulczynski, Simple Matching, Levenshtein

Upvotes: 3

Ishtar

Reputation: 11662

Hamming distance

Upvotes: 1

How many kinds of Distance Function can we use?

Answers (4)

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