T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation

An R wrapper around the fast T-distributed Stochastic Neighbor Embedding implementation by Van der Maaten (see < https://github.com/lvdmaaten/bhtsne/> for more information on the original implementation).


CRAN version Travis-CI Build Status codecov.io CRAN mirror downloads

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) # Plot the result

Details

This R package offers a wrapper around the Barnes-Hut TSNE C++ implementation of [2] [3]. Only minor changes were made to the original code to allow it to function as an R package.

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. Barnes-Hut-SNE. In Proceedings of the International Conference on Learning Representations, 2013.

[3] http://homepage.tudelft.nl/19j49/t-SNE.html

News

Reference manual

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install.packages("Rtsne")

0.15 by Jesse Krijthe, 3 months ago


https://github.com/jkrijthe/Rtsne


Browse source code at https://github.com/cran/Rtsne


Authors: Jesse Krijthe [aut, cre] , Laurens van der Maaten [cph] (Author of original C++ code)


Documentation:   PDF Manual  


file LICENSE license


Imports Rcpp, stats

Suggests irlba, testthat

Linking to Rcpp


Imported by CINNA, FateID, PAC, RaceID, Rdimtools, Seurat, Spectrum, densityClust, diceR, projector, randomcoloR, scRNAtools, visvow.

Suggested by coRanking, dimRed, stm, themetagenomics.


See at CRAN