New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

k-means should allow selecting points randomly as initialization #596

Closed
rcurtin opened this Issue Mar 26, 2016 · 1 comment

Comments

Projects
None yet
1 participant
@rcurtin
Member

rcurtin commented Mar 26, 2016

This also comes out of the discussion for #592. @kno10's suggestion is that we simply pick points randomly from the dataset as initial centroids.

This requires a bit of refactoring because the current initialization policy operates by setting the assignments of each point, instead of the location of each centroid. So there will need to be a little bit of thought on how exactly to handle this, but probably some template metaprogramming to handle both cases is in order here (so that a user can both write initialization policies that give initial point assignments and also initial centroids).

I will do this as I have time.

@rcurtin rcurtin self-assigned this Mar 26, 2016

@rcurtin rcurtin added this to the mlpack 2.0.2 milestone Mar 26, 2016

@rcurtin

This comment has been minimized.

Show comment
Hide comment
@rcurtin

rcurtin Apr 12, 2016

Member

This has been done in a38608b and the k-means program now defaults to this type of initialization. Thanks again @kno10 for pointing this out. :)

Member

rcurtin commented Apr 12, 2016

This has been done in a38608b and the k-means program now defaults to this type of initialization. Thanks again @kno10 for pointing this out. :)

@rcurtin rcurtin closed this Apr 12, 2016

@rcurtin rcurtin added the R: fixed label Apr 12, 2016

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment