repo <https://github.com/rvw-org/rvw-legacy> can provide an alternative using

Description: R interface to Vowpal Wabbit fast out-of-core learning
system The Vowpal Wabbit (VW) project is a fast out-of-core
learning system sponsored by Yahoo! Research and written by
John Langford along with a number of contributors.
There are two ways to have a fast learning algorithm: (a) start with a
slow algorithm and speed it up, or (b) build an intrinsically
fast learning algorithm. This project is about approach (b),
and it has reached a state where it may be useful to others as
a platform for research and experimentation.
There are several optimization algorithms available with the baseline
being sparse gradient descent (GD) on a loss function (several
are available). The code should be easily usable. Its only
external dependence is on the Boost library, which is often

This R package does not include the distributed computing
implementation of the cluster/ directory of the upstream
sources.  Use of the software as a network servie is also not
directly supported as the aim is a simpler direct call from R

Description: R interface to Vowpal Wabbit fast out-of-core learning system
The Vowpal Wabbit (VW) project is a fast out-of-core learning system
sponsored by Yahoo! Research and written by John Langford along with a
There are two ways to have a fast learning algorithm: (a) start with a slow
algorithm and speed it up, or (b) build an intrinsically fast learning
algorithm. This project is about approach (b), and it has reached a state
where it may be useful to others as a platform for research and
There are several optimization algorithms available with the baseline being
sparse gradient descent (GD) on a loss function (several are available). The
code should be easily usable. Its only external dependence is on the Boost
library, which is often installed by default.
This R package does not include the distributed computing implementation of
the cluster/ directory of the upstream sources.  Use of the software as a
network servie is also not directly supported as the aim is a simpler direct
call from R for validation and comparison.