Best data structure for high dimensional nearest neighbor search
问题 I'm actually working on high dimensional data (~50.000-100.000 features) and nearest neighbors search must be performed on it. I know that KD-Trees has poor performance as dimensions grows, and also I've read that in general, all space-partitioning data structures tends to perform exhaustive search with high dimensional data. Additionally, there are two important facts to be considered (ordered by relevance): Precision: The nearest neighbors must be found (not approximations). Speed: The