R wrapper for Van der Maaten’s Barnes-Hut implementation of t-Distributed Stochastic Neighbor Embedding
To install from CRAN:
install.packages("Rtsne") # Install Rtsne package from CRANTo install the latest version from the github repository, use:
if(!require(devtools)) install.packages("devtools") # If not already installed
devtools::install_github("jkrijthe/Rtsne")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
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.
[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.