README.md

README.md

@@ -9,7 +9,7 @@
 import "github.com/keilerkonzept/bitknn"
 ```
 
-`bitknn` is a fast [k-nearest neighbors (k-NN)](https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm) library for `uint64`s, using Hamming distance to measure similarity.
+`bitknn` is a fast [k-nearest neighbors (k-NN)](https://en.wikipedia.org/wiki/K-nearest_neighbors_algorithm) library for `uint64`s, using (bitwise) Hamming distance.
 
 If you need to classify **binary feature vectors that fit into `uint64`s**, this library might be useful. It is fast mainly because we can use cheap bitwise ops (XOR + POPCNT) to calculate distances between `uint64` values. For smaller datasets, the performance of the [neighbor heap](heap.go) is also relevant, and so this part has been tuned here also.