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: 2022-12-07
Last Published: 2022-12-03
Machine Learning in Rust.
Last Commit: 2022-11-22
Last Published: 2022-11-09
High-level bindings for Faiss, the vector similarity search engine
Last Commit: 2022-12-14
Last Published: 2022-03-28
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
Generic implementations of clustering algorithms. Includes k-means, DBSCAN and OPTICS.
Last Commit: 2017-10-07
Last Published: 2015-12-15
k-Medoids clustering with the FasterPAM algorithm
Last Commit: 2022-09-24
Last Published: 2022-09-24
A library for doing maching learning in Rust.
Last Commit: 2022-06-15
Last Published: 2018-01-31
Rust library for Self Organising Maps (SOM).
Last Commit: 2022-10-15
Last Published: 2020-04-01
A k -Deviation Density Based Clustering Algorithm (kDDBSCAN)
Last Commit: 2020-06-13
Last Published: 2020-06-13