**RTextTools: a machine learning library for text classification - Blog**, and kindly contributed to R-bloggers)

*/inst/examples/*directory of the RTextTools source code.

Since its introduction at the 2011 Comparative Agendas Project Conference in Catania, Italy, the RTextTools team has refined the API and implemented a number of features. Some of these features include n-gram analysis, text labels, comprehensive analytics, and a streamlined interface. Our plan for the year ahead includes a major overhaul of the nine algorithms to facilitate low-memory ensemble classification. However, this goal involves more than just the RTextTools team; it requires the R machine learning community to strive for efficient supervised learning algorithms. Many R packages do not utilize compressed sparse matrices, and therefore are limited in their applications for large-N data-sets. Therefore, we aim to promote efficient practices by package developers and write several implementations of our own to push the capabilities of statistical computing in R.

Thank you for all your feedback and support as we look forward to another productive year in 2012!

**leave a comment**for the author, please follow the link and comment on their blog:

**RTextTools: a machine learning library for text classification - Blog**.

R-bloggers.com offers

**daily e-mail updates**about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...