module Knntest: sig .. end
Tests the KNN tree on some random points in high-dimensional
space, comparing the distance to the closest point found
(using both balanced and unbalanced trees) to the distance
to the actual closest point.
val random_float_list : int -> float list
A random list of floats.
val random_data : int -> int -> (float list * int) list
Makes up random data, as a list of points in d-dimensional space,
each paired with a distinct integer.
val dist : float list -> float list -> float
Euclidean distance.
module Params: sig .. end
Example nearest-neighbor parameters.
module T: Knn.Make(Params)
val print_floats : float list -> unit
val run_test : int -> int -> float -> int -> unit
Runs the test for a given number of points, and search width.