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Package hyper allows fast approximate search of nearest neighbour vectors in n-dimensional space. It does not have any dependencies.
Package functions discretize a vector and generate a set of hashes, as described in the [following document](https://vitali-fedulov.github.io/algorithm-for-hashing-high-dimensional-float-vectors.html).
Package functions discretize a vector and generate a set of hashes, as described [here](https://vitali-fedulov.github.io/algorithm-for-hashing-high-dimensional-float-vectors.html) (also as [PDF](https://github.com/vitali-fedulov/research/blob/main/Algorithm%20for%20hashing%20float%20vectors.pdf)).
To use the package follow the sequence of functions/methods:
1) CubeSet or CentralCube, depending which one is used for a database record and which one for a query.