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My intuition is that so long as the magnitude that dimensions are weighted with is similar, the most likely sources of loss/differences between VCS and KNN would be:

1. Non-linear spacing of segments in the VCS. In order to achieve maximally similar results between methods, you need to preform transforms on the dimensions to approximate the result of any non-linear spacing of segments in the VCS.
2. Insufficient number of KNN data points used when the data is dense (late in battle). How many data points should be used should probably be larger as the data becomes denser. The density of points returned should probably affect how many points are used.

Have you looked into these factors Skilgannon?

I'm going to try the non-linear thing just now - good call as I had forgotten about this despite spending quite a while tuning it in my gun.

I'm currently weighting based on distance to the location point as a function of the average distance of the closest 3 points - it works quite well but I wouldn't be surprised if there were improvements which could be made.