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You could try looking at the density of complaints in an area, even though that could be computationally intensive. It would give you some idea of where the 'clumps' are.

To find the rough edges of the clumps, find the number of complaints in a small radius, then increase the radius and see how many more you get. At some point the program will have to make the call as to whether or not it is worth expanding the circle to include the extra few points, which is a classical calculus problem.

You would also have to include extra rules to stop the circle from increasing forever or shrinking to nothing.

Other techniques might involve randomly (or less than randomly) drawing circles around the centre of the clump and seeing which ones catch the most complaints, then declaring the union of all the circles to be the clump.

I didn't believe in evil until I dated it.

In reply to Re: Sorting by geographical proximity / clumping groups of items based on X and Y by jepri
in thread Sorting by geographical proximity / clumping groups of items based on X and Y by vroom

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