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R wrapper for Van der Maaten’s Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding

Installation

To install from CRAN:

install.packages("Rtsne") # Install Rtsne package from CRAN

To install the latest version from the github repository, use:

if(!require(devtools)) install.packages("devtools") # If not already installed
devtools::install_github("jkrijthe/Rtsne")

Usage

After installing the package, use the following code to run a simple example (to install, see below).

library(Rtsne) # Load package
iris_unique <- unique(iris) # Remove duplicates
set.seed(42) # Sets seed for reproducibility
tsne_out <- Rtsne(as.matrix(iris_unique[,1:4])) # Run TSNE
plot(tsne_out$Y,col=iris_unique$Species,asp=1) # Plot the result

Details

This R package offers a wrapper around the Barnes-Hut TSNE C++ implementation of [2] [3]. Changes were made to the original code to allow it to function as an R package and to add additional functionality and speed improvements.

References

[1] L.J.P. van der Maaten and G.E. Hinton. “Visualizing High-Dimensional Data Using t-SNE.” Journal of Machine Learning Research 9(Nov):2579-2605, 2008.

[2] L.J.P van der Maaten. “Accelerating t-SNE using tree-based algorithms.” Journal of Machine Learning Research 15.1:3221-3245, 2014.

[3] https://lvdmaaten.github.io/tsne/

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.