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joshlk avatar joshlk commented on June 16, 2024 1

No it does not. But if you want to hack your own solution you can try changing this line:

D = euclidean_distances(X, C, squared=False)

from k-means-constrained.

amks1 avatar amks1 commented on June 16, 2024

Thanks. Sorry if this is a dumb question, but are the cluster centers chosen from the set of input points?

from k-means-constrained.

bibblybobblyben avatar bibblybobblyben commented on June 16, 2024

Hi - thanks for your work building this package. I have also come across the question of trying to implement a custom distance metric in the clustering so have opened a PR to address it. Happy to be corrected if this is not a desirable change in the main package.

from k-means-constrained.

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