LiblineaR.ACF: Linear Classification with Online Adaptation of Coordinate
Frequencies
Solving the linear SVM problem with coordinate descent
is very efficient and is implemented in one of the most often used packages,
'LIBLINEAR' (available at http://www.csie.ntu.edu.tw/~cjlin/liblinear).
It has been shown that the uniform selection of coordinates can be
accelerated by using an online adaptation of coordinate frequencies (ACF).
This package implements ACF and is based on 'LIBLINEAR' as well as
the 'LiblineaR' package (<https://cran.r-project.org/package=LiblineaR>).
It currently supports L2-regularized L1-loss as well as L2-loss linear SVM.
Similar to 'LIBLINEAR' multi-class classification (one-vs-the rest, and
Crammer & Singer method) and cross validation for model selection is
supported. The training of the models based on ACF is much faster than
standard 'LIBLINEAR' on many problems.
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