What distance measure does centroid based meanshift algorithm uses for clustering?

Question

I have a sparse TruncatedSVD matrices with 810 * 74 dimensions. I am trying to cluster with centroid-based MeanShift algorithm using sklearn api. However, I could not find information about the distance measure that meanshift uses by default neither in sklearn documentation nor in online blogs. There is no option to provide a precomputed distance matrices too. Does Meanshift caluculates Euclidean distance by default before doing centroid based computation?

Gone through sklearn documentation - https://scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html

Also searched online but without a luck

Answer 1

It's not using distances directly.

It's using the RBF kernel, which does however contain something akin to Euclidean distance inside.

I doubt this is a good choice for 74 dimensional data.