K-Means in Rust

Parallel K-Means implementation written in Rust.
See here for the definition of a problem and possible algorithm implementations.

Building

In case you don't have Rust toolchain installed, use Rustup to quickly setup it. Then just run cargo build --release inside the repo directory. The resulting binary will be available in ./target/release/k-means.

Alternatively, you can use static binary which should work out of the box on any x86_64 GNU/Linux system.

Running

In order to test whether the binary works try sets in test-datasets folder. The results should be like this:

$ ./target/release/k-means --clusters=2 --threads=4 test-datasets/small.txt
Data file read successfully, took 1 milliseconds
Commencing K-Means clustering, searching 2 clusters in 4000 points
K-Means converged after 2 iterations, took 0 milliseconds
Cluster 0: centroid coordinates: [180.01707500000012, 18.29], cluster size: 800
Cluster 1: centroid coordinates: [50.047634375000015, 8.82875], cluster size: 3200

License

Copyright (C) 2016-2019  Oleg `Kanedias` Chernovskiy

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.