Crate linfa_reduction

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

utils

Structs

DiffusionMap

Embedding of diffusion map technique

DiffusionMapParams

Diffusion map hyperparameters

DiffusionMapValidParams

Diffusion map hyperparameters

Pca

Fitted Principal Component Analysis model

PcaParams

Pincipal Component Analysis parameters

Enums

ReductionError

Type Definitions

Result