#machine-learning #factorization #linfa #unsupervised

linfa-ica

A collection of Independent Component Analysis (ICA) algorithms

9 releases (5 breaking)

0.7.0 Oct 16, 2023
0.6.1 Dec 3, 2022
0.6.0 Jun 15, 2022
0.5.1 Mar 1, 2022
0.2.1 Nov 29, 2020

#857 in Machine learning

Download history 1/week @ 2024-02-13 7/week @ 2024-02-20 7/week @ 2024-02-27 1/week @ 2024-03-05 3/week @ 2024-03-12 10/week @ 2024-03-26 48/week @ 2024-04-02

58 downloads per month

MIT/Apache

290KB
4K SLoC

Independent Component Analysis (ICA)

linfa-ica aims to provide pure Rust implementations of ICA algorithms.

The Big Picture

linfa-ica 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 scikit-learn.

Current state

linfa-ica currently provides an implementation of the following factorization methods:

  • Fast Independent Component Analysis (FastICA)

Examples

There is an usage example in the examples/ directory. To run, use:

$ cargo run --release --example fast_ica

BLAS/Lapack backend

See this section to enable an external BLAS/LAPACK backend.

License

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.

Dependencies

~5–15MB
~229K SLoC