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Clustering
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.
You can also find an introduction to distribution-based clustering using Gaussian mixture models in rusty-machine in this post: Using GMMs in Rust
kmeans-colors [ crate · repo · docs ]
Simple k-means clustering to find dominant colors in images. Backed by a generic k-means implementation offered as a standalone library.
rusty-machine [ crate · repo · docs ]
A machine learning library.
faiss [ crate · repo · docs ]
High-level bindings for Faiss, the vector similarity search engine
cogset [ crate · repo · docs ]
Generic implementations of clustering algorithms. Includes k-means, DBSCAN and OPTICS.
smartcore [ crate · repo · docs ]
The most advanced machine learning library in rust.
rusticsom [ crate · repo · docs ]
Rust library for Self Organising Maps (SOM).
linfa [ crate · repo · docs ]
A Machine Learning framework for Rust
kddbscan [ crate · repo · docs ]
A k -Deviation Density Based Clustering Algorithm (kDDBSCAN)
rustml [ crate · repo · docs ]
A library for doing maching learning in Rust.
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