The Rust machine learning ecosystem is a bit shallow on cluster analysis,
but you can find implementations of k-means, DBSCAN, and OPTICS algorithms
scattered between the crates below.
The Rust-ML book has walkthroughs for
linfa's DBSCAN and KMeans implementations here.
A Machine Learning framework for Rust
Last Commit: 2022-05-09
Last Published: 2022-02-27
High-level bindings for Faiss, the vector similarity search engine
Last Commit: 2022-05-15
Last Published: 2022-03-28
The most advanced machine learning library in rust.
Last Commit: 2022-05-12
Last Published: 2022-05-09
Simple k-means clustering to find dominant colors in images.
Backed by a generic k-means implementation offered as a standalone library.
Last Commit: 2022-03-17
Last Published: 2022-03-17
A machine learning library.
Last Commit: 2020-07-10
Last Published: 2017-01-06
k-Medoids clustering with the FasterPAM algorithm
Last Commit: 2022-04-15
Last Published: 2022-03-27
Generic implementations of clustering algorithms. Includes k-means, DBSCAN and OPTICS.
Last Commit: 2017-10-07
Last Published: 2015-12-15
A library for doing maching learning in Rust.
Last Commit: 2018-01-31
Last Published: 2018-01-31
Rust library for Self Organising Maps (SOM).
Last Commit: 2020-10-14
Last Published: 2020-04-01
A k -Deviation Density Based Clustering Algorithm (kDDBSCAN)
Last Commit: 2020-06-13
Last Published: 2020-06-13