我可以对kmeans功能使用自定义距离度量吗？

Question

I am using the function, kmeans, to perfrom K-means clustering.

I have a special data which need a custom distance measure function and custom mean function.

Can I put (1) a custom distance measure function and (2) custom mean function to the kmeans function?

It seems it uses Euclidean measure only.

Answer 1

The standard kmeans does not allow this, for good reasons. It uses some clever algorithms (Hartigan and Wong; which is why it is much faster than the standard Lloyd textbook algorithm you find in about 100 other R packages). But these only work for the classic k-means scenario with squared deviations (which means assigning each cluster to the Euclidean nearest center, but it actually optimizes least-squares, not Euclidean distances).

I doubt you can simply plug in other distances and centroid functions into the Hartigan and Wong method (apart from it being written in Fortran, so you cannot just plug in a R function there anyway).

Beware that there are very few known combinations where other distances and means are known to always converge well. Bregman divergences should be fine, and cosine is equivalent to squared Euclidean on a sphere, so it will also work.