[P] New benchmarks for approximate nearest neighbors • r/MachineLearning

Then you compare a number of ANN algorithms on that on a number of data-sets (each comes with a pre-selected distance metric for the exhaustive nearest neighbour search, while the approximative algorithms may or may not use the same metric but are compared to it). I have indeed not seen many empirical tests comparing the approximate nearest neighbour to the actual precomputed nearest neighbour. What I have seen however are empirical tests where you use nearest neighbour search as a subroutine in some classification algorithm or other and where the classification performance results of the algorithm with (impractical) exhaustive search are tested against a variant with approximative search. Do you think testing only ANN against exhaustive 1NN is sufficient no matter what the techniques get used for? Apparently, you don't think just testing it through the outcome in the application scenario is sufficient, but maybe both then?