LIBLINEAR is a software library for large data sets classification and regression. The original software in C/C++ is developed and maintained by Prof. Chih-Jen Lin and his team at the Machine Learning Group of the Taiwan University. Be it of cases where data have a large number of observations with a limited number of features describing each observations or, in the context of clinical research, a limited number of observations (patients, generally) described by a very high number of features (candidate markers), LIBLINEAR will do the job.
As most of our developments are done in the open source R language and R language is a very common development language in the biostatistics/bioinformatics/data mining community, we decided to develop and maintain the R library LiblineaR, making all the functionalities of the original LIBLINEAR library available in the R environment. This software library thus offers to bioinformaticians, machine learners, data miners, to process data sets with very large number of features and/or large number of observations right in their favorite language. Recent versions of our package offers not only support for classification, but also for regression. The use of sparse matrices is also supported. As an open source software, it is freely available.