# “Reverse Clustering” Algorithm?

The clustering algorithm splits points into disjoint sets in a way that minimizes the intra-set distance.

Is there an efficient algorithm which does the opposite (maximize the intra-set distance)? I.E. I would like the points in each set to be as "spread out" as possible.

• How exactly do you want to define the intra-set distance ? And how do you want to control the number of clusters ? – Yves Daoust Aug 7 '18 at 10:02

I don’t get the question. To me that doesn’t make much sense. By definition if d is a distance and x a vector $d(x,x)=0$. How would you deal with it then ? x could not even belong to its own cluster.
• The fact that $d(x,x)=0$ forbids in no way a point to belong in a cluster ! – Yves Daoust Aug 7 '18 at 10:01