Unformatted text preview: now for K-means 1 set the number of clusrers =k 2) choose k starting points ato be used as initial centroids (1st k point, last k, point k, random points) 3) examine each point and allocate it to the clusrter whose centroid is nearest. 4) recalculate the cluster centroid after each addition Homework 158 34 128 *015 23 33 *017 26 *019 *019 *016 do an MST and a Kmeans (with 4) due tuesday...
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- Spring '08
- Standard Deviation, std dev, clusrers =k, #cluster, #clusters