8 releases (5 breaking)
|0.6.0||Jun 15, 2022|
|0.5.1||Mar 1, 2022|
|0.5.0||Oct 21, 2021|
|0.4.0||Apr 28, 2021|
|0.1.0||Nov 23, 2019|
#12 in Machine learning
1,747 downloads per month
Used in 3 crates (via egobox-moe)
linfa-clustering aims to provide pure Rust implementations of popular clustering algorithms.
linfa-clustering is a crate in the
linfa ecosystem, an effort to create a toolkit for classical Machine Learning implemented in pure Rust, akin to Python's
You can find a roadmap (and a selection of good first issues) here - contributors are more than welcome!
linfa-clustering currently provides implementation of the following clustering algorithms, in addition to a couple of helper functions:
- Approximated DBSCAN
- Gaussian Mixture Model
Implementation choices, algorithmic details and a tutorial can be found here.
WARNING: Currently the Approximated DBSCAN implementation is slower than the normal DBSCAN implementation. Therefore DBSCAN should always be used over Approximated DBSCAN.
See this section to enable an external BLAS/LAPACK backend.
Dual-licensed to be compatible with the Rust project.
Licensed under the Apache License, Version 2.0 http://www.apache.org/licenses/LICENSE-2.0 or the MIT license http://opensource.org/licenses/MIT, at your option. This file may not be copied, modified, or distributed except according to those terms.