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Hmmm, I weight each hit based on the inverse distance that the KNN point had to the current point, so I don't have that problem. I'm just thinking, that isn't made equal on a per-enemy basis, so if one enemy has KNN points closer together its points will be weighted higher. Hrmmm... at the same time surely those shots are of a higher certainty? Will need to test.

Maybe inverse distance is overflowing kernel density estimation. When KNN distance is too low, classification score tends to infinity. The result is a bunch of tied angles with infinity classification score. Depending on the tie-breaking being used, the gun can trash a lot too.