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
High-level bindings for Faiss, the vector similarity search engine
Machine Learning in Rust.
Simple k-means clustering to find dominant colors in images. Backed by a generic k-means implementation offered as a standalone library.
k-Medoids clustering with the FasterPAM algorithm
A machine learning library.
easy way to perform kmeans clustering on arbitrary data
Generic implementations of clustering algorithms. Includes k-means, DBSCAN and OPTICS.
A library for doing maching learning in Rust.
Rust library for Self Organising Maps (SOM).
A k -Deviation Density Based Clustering Algorithm (kDDBSCAN)
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