Crate linfa_reduction
source · [−]Expand description
Dimensional Reduction
linfa-reduction
aims to provide pure Rust implementations of dimensional reduction algorithms.
The Big Picture
linfa-reduction
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-reduction
currently provides an implementation of the following dimensional reduction methods:
- Diffusion Mapping
- Principal Component Analysis (PCA)
Examples
There is an usage example in the examples/
directory. To run, use:
$ cargo run --release --example diffusion_map
$ cargo run --release --example pca
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.
Modules
Structs
Embedding of diffusion map technique
Diffusion map hyperparameters
Diffusion map hyperparameters
Fitted Principal Component Analysis model
Pincipal Component Analysis parameters