I'd like to announce the availability of the "tsne" package. It provides the T distributed Stocastic Neighbor Embedding algorithm by van der Maaten and Hinton:
1. http://ict.ewi.tudelft.nl/~lvandermaaten/t-SNE.html 2. 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. [ PDF<http://ict.ewi.tudelft.nl/%7Elvandermaaten/t-SNE_files/vandermaaten08a.pdf>] [ Supplemental Material<http://ict.ewi.tudelft.nl/%7Elvandermaaten/t-SNE_files/SupplementalMaterial.pdf>(24MB) ] 3. L.J.P. van der Maaten. Learning a Parametric Embedding by Preserving Local Structure. In Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS), JMLR W&CP 5:384-391, 2009. [ PDF<http://ict.ewi.tudelft.nl/%7Elvandermaaten/t-SNE_files/Paper.pdf>] It has a few utility/convenience parameters for tweaking the algorithm and providing feedback. Be sure to try the example to get an idea of how it works: require(tsne) ?tsne It's currently much slower than the "official" implementations by van der Maaten. If you're interested in providing some tips on optimized C/Fortan code, let me know. Best, -Justin -- Justin Donaldson PhD Candidate, Informatics Indiana University http://www.scwn.net aim: iujjd twitter: jjdonald [[alternative HTML version deleted]] _______________________________________________ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.