Python offers two nearest neighbor regressions: radius nearest neighbor and k-nearest neighbor. I'm trying to figure out a few things: 1. Under which circumstances would each be preferable? 2. How do you approach setting the optimal radius or k value?
For reference, I'm working with a relatively sparse data set with a uniform geometry. As time passes, that dataset will get less sparse, but will continue to have a relatively uniform geometry.
Thanks for any help.