linfa-tsne provides a pure Rust implementation of exact and Barnes-Hut t-SNE.
linfa-tsne 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
linfa-tsne currently provides an implementation of the following methods:
- exact solution t-SNE
- Barnes-Hut t-SNE
It wraps the bhtsne crate, all kudos to them.
There is an usage example in the
examples/ directory. To run it, do:
$ cargo run --example tsne
You have to install the
gnuplot library for plotting. Also take a look at the README to see what BLAS/LAPACK backends are possible.
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.
- The t-SNE algorithm is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map.
- Error variants from hyper-parameter construction or model estimation
TSneErroras error type