Friday, June 23, 2006

K-Means Clustering

Basic Algorithm
1. Choose k cluster centers at random
2. Assign each point to nearest cluster center
3. Compute the new cluster centers based on the assigned points
4. Repeat until cluster centers converge

Shortcomings
Finds local minima
The random placement of cluster centers affects the outcome

Here is a nice K-Means Demo

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