Reputation:
I wonder what kind of seed selection methods I can apply to K-means algorithm. Google search wasn't that helpful. Any suggestions?
Upvotes: 2
Views: 1361
Reputation: 10139
The seeds depend on the domain. For example, if your data items are words, your seeds should be the most frequent words. Otherwise, you could cluster a small sample and use that as a seed.
Here is an example of a more sophisticated algorithm:
Single Pass Seed Selection Algorithm for k-Means. K. Karteeka Pavan, Allam Appa Rao, A.V. Dattatreya Rao and G.R. Sridhar. Journal of Computer Science 6 (1): 60-66, 2010. pdf
Upvotes: 2
Reputation: 17648
Google for "supervised" k means clustering & k++ means.... also specify your performance needs ( whats your k? how many input points?)
In general, a few thousand points can easily be clustered w a naive k means algorithm implementation... So I would try that first.
Also, if your not sure what K should be, try MCL clustering first to get a good estimate.
Upvotes: 1