k-means in R, usage of nstart parameter? I try to use k-means clusters (using SQLserver + R), and it seems that my model is not stable : each time I run the k-means algorithm, it finds different clusters. But if I set nstart (in R k-means function) high enough (10 or more) it becomes stable. 

The default value for this parameter is 1 but it seems that setting it to a higher value (25) is recommended (I think I saw somewhere in the documentation).

So I'm a bit confused...
Any advice ?
nstart option attempts multiple initial configurations and reports on the best one. For example, adding nstart=25 will generate 25 initial random centroids and choose the best one for the algorithm. Hope this helps!

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