5 packages on CRAN
Extreme Gradient Boosting, which is an efficient implementation of the gradient boosting framework from Chen & Guestrin (2016) <doi:10.1145/2939672.2939785>. This package is its R interface. The package includes efficient linear model solver and tree learning algorithms. The package can automatically do parallel computation on a single machine which could be more than 10 times faster than existing gradient boosting packages. It supports various objective functions, including regression, classification and ranking. The package is made to be extensible, so that users are also allowed to define their own objectives easily.
Three ensemble learning algorithms based on support vector machines. They all train support vector machines on subset of data and combine the result.
R Interface to Pullword Service for natural language processing in Chinese. It enables users to extract valuable words from text by deep learning models. For more details please visit the official site (in Chinese) http://pullword.com/.
R interface to the 'LTP'-Cloud service for Natural Language Processing in Chinese (http://www.ltp-cloud.com/).
High dimensional testing procedures on mean, covariance and white noises.