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Weighted k means clustering

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Peter
Peter on 23 Oct 2013
Commented: Royi Avital on 9 Aug 2015
Hey all,
I am using Matlab for a geostatistical project.
I use coordinates of renewable energy facilities and try to optimize the electricity grid by clustering the facilities and finding the coordinates of some new electricity substations (cluster centroids).
I used to do that using k means algorithm.
Now I need to take into account the coordinates of the existing electricity substations and I need to use them with some weight, so the new substations will get closer to the old ones.
Does anybody know a way to use weight in k means? I found f kmeans algorithm, but I think it doesn't work really the way I need it to work.
Any ideas?
  1 Comment
Royi Avital
Royi Avital on 9 Aug 2015
I tried it myself as well. It seems something doesn't work there.

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Answers (1)

Royi Avital
Royi Avital on 8 Aug 2015
Usually the weighting would be using Mahalanobis Distance Matrix.
If I'm correct about the file you linked, it uses a distance matrix which is Diagonal.
The Diagonal is determined by the weight vector.
  1 Comment
Royi Avital
Royi Avital on 9 Aug 2015
I tried it myself as well. It seems something doesn't work there.

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