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//! `linfa-clustering` aims to provide pure Rust implementations //! of popular clustering algorithms. //! //! ## The big picture //! //! `linfa-clustering` is a crate in the `linfa` ecosystem, a wider effort to //! bootstrap a toolkit for classical Machine Learning implemented in pure Rust, //! kin in spirit to Python's `scikit-learn`. //! //! You can find a roadmap (and a selection of good first issues) //! [here](https://github.com/LukeMathWalker/linfa/issues) - contributors are more than welcome! //! //! ## Current state //! //! Right now `linfa-clustering` only provides a single algorithm, `K-Means`, with //! a couple of helper functions. //! //! Implementation choices, algorithmic details and a tutorial can be found [here](struct.KMeans.html). //! //! Check [here](https://github.com/LukeMathWalker/clustering-benchmarks) for extensive benchmarks against `scikit-learn`'s K-means implementation. mod appx_dbscan; mod dbscan; mod gaussian_mixture; #[allow(clippy::new_ret_no_self)] mod k_means; mod utils; pub use appx_dbscan::*; pub use dbscan::*; pub use gaussian_mixture::*; pub use k_means::*; pub use utils::*;