# Clustering
`linfa-clustering` aims to provide pure Rust implementations of popular clustering algorithms.
## The big picture
`linfa-clustering` is a crate in the [`linfa`](https://crates.io/crates/linfa) ecosystem, an effort to create a toolkit for classical Machine Learning implemented in pure Rust, akin to Python's `scikit-learn`.
You can find a roadmap (and a selection of good first issues)
[here](https://github.com/rust-ml/linfa/issues) - contributors are more than welcome!
## Current state
`linfa-clustering` currently provides implementation of the following clustering algorithms, in addition to a couple of helper functions:
- K-Means
- DBSCAN
Implementation choices, algorithmic details and a tutorial can be found
[here](https://docs.rs/linfa-clustering).
Check [here](https://github.com/LukeMathWalker/clustering-benchmarks) for extensive benchmarks against `scikit-learn`'s K-means implementation.
## License
Dual-licensed to be compatible with the Rust project.
Licensed under the Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 or the MIT license http://opensource.org/licenses/MIT, at your option. This file may not be copied, modified, or distributed except according to those terms.