bhtsne

Barnes-Hut implementation of t-SNE written in Rust. The algorithm is described with fine detail in this paper by Laurens van der Maaten.

Installation

Add this line to your Cargo.toml: toml [dependencies] bhtsne = "0.3.1"

Example

```rust use bhtsne;

// Parameters template. let n: usize = 8; // Number of vectors to embed. let d: usize = 4; // The dimensionality of the original space. let theta: f32 = 0.5; // The parameter used by the Barnes-Hut algorithm. When set to 0.0 // the exact t-SNE version is used instead.

let perplexity = 1.0; // The perplexity of the conditional distribution. let maxiter = 2000; // The number of fitting iterations. let nodims = 2; // The dimensionality of the embedded space.

// Loads data the from a csv file skipping the first row, // treating it as headers and skipping the 5th column, // treating it as a class label. let mut data: Vec = bhtsne::loadcsv("data.csv", true, Some(4)); // This is the vector for the resulting embedding. let mut y: Vec = vec![0.0; n * nodims]; // Runs t-SNE. bhtsne::run( &mut data, n, d, &mut y, nodims, perplexity, theta, false, maxiter, 250, 250, ); // Writes the embedding to a csv file. bhtsne::writecsv("embedding.csv", y, nodims); ``` Also check the docs available on crates.io.

MNIST embedding

The following embedding has been obtained by preprocessing the MNIST dataset using PCA to reduce its dimensionality to 50. It took approximately 17 mins on a 2.0GHz quad-core 10th-generation i5 MacBook Pro.