RVowpalWabbit: R interface to the Vowpal Wabbit
Version 0.0.6

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 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.

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AuthorDirk Eddelbuettel <edd@debian.org>
Date of publication2014-01-05 21:04:42
MaintainerDirk Eddelbuettel <edd@debian.org>
LicenseGPL (>= 2)
Version0.0.6
URL https://github.com/JohnLangford/vowpal_wabbit/ http://dirk.eddelbuettel.com/code/rcpp.html
Package repositoryView on R-Forge
InstallationInstall the latest version of this package by entering the following in R:
install.packages("RVowpalWabbit", repos="http://R-Forge.R-project.org")

Getting started

Man pages

vw: Run the Vowpal Wabbit fast out-of-core learner

Functions

vw Man page Source code

Files

ChangeLog
DESCRIPTION
NAMESPACE
R
R/vw.R
cleanup
configure
configure.in
demo
demo/00Index
demo/vw.R
inst
inst/test
inst/test/README
inst/test/README.R-package
inst/test/RunTests
inst/test/models
inst/test/models/0001.model
inst/test/models/0002.model
inst/test/models/0002a.model
inst/test/models/0002c.model
inst/test/pred-sets
inst/test/pred-sets/ref
inst/test/pred-sets/ref/0001.predict
inst/test/pred-sets/ref/0002b.predict
inst/test/pred-sets/ref/0002c.predict
inst/test/test-sets
inst/test/test-sets/0001.dat
inst/test/test-sets/ref
inst/test/test-sets/ref/0001.stderr
inst/test/test-sets/ref/0001.stdout
inst/test/test-sets/ref/0002b.stderr
inst/test/test-sets/ref/0002b.stdout
inst/test/test-sets/ref/0002c.stderr
inst/test/test-sets/ref/0002c.stdout
inst/test/train-sets
inst/test/train-sets/0001.dat
inst/test/train-sets/0001.dat.cache
inst/test/train-sets/0002.dat
inst/test/train-sets/ref
inst/test/train-sets/ref/0001.stderr
inst/test/train-sets/ref/0001.stdout
inst/test/train-sets/ref/0002.stderr
inst/test/train-sets/ref/0002.stdout
inst/test/train-sets/ref/0002a.stderr
inst/test/train-sets/ref/0002a.stdout
inst/test/train-sets/ref/0002c.stderr
inst/test/train-sets/ref/0002c.stdout
inst/test/train-sets/ref/wiki1K.stderr
inst/test/train-sets/ref/wiki1K.stdout
inst/test/train-sets/wiki1K.dat
man
man/vw.Rd
src
src/Makevars.in
src/R_vw.cpp
src/accumulate.cc
src/accumulate.h
src/active_interactor.cc
src/allreduce.cc
src/allreduce.h
src/bfgs.cc
src/bfgs.h
src/cache.cc
src/cache.h
src/comp_io.h
src/constant.h
src/delay_ring.cc
src/delay_ring.h
src/example.h
src/gd.cc
src/gd.h
src/gd_mf.cc
src/gd_mf.h
src/global_data.cc
src/global_data.h
src/hash.cc
src/hash.h
src/io.cc
src/io.h
src/lda_core.cc
src/lda_core.h
src/loss_functions.cc
src/loss_functions.h
src/message_relay.cc
src/message_relay.h
src/multisource.cc
src/multisource.h
src/network.cc
src/network.h
src/noop.cc
src/noop.h
src/parse_args.cc
src/parse_args.h
src/parse_example.cc
src/parse_example.h
src/parse_primitives.cc
src/parse_primitives.h
src/parse_regressor.cc
src/parse_regressor.h
src/parser.cc
src/parser.h
src/sender.cc
src/sender.h
src/simple_label.cc
src/simple_label.h
src/sparse_dense.cc
src/sparse_dense.h
src/unique_sort.cc
src/unique_sort.h
src/unused
src/unused/main.cc
src/unused/offset_tree.cc
src/v_array.h
src/vw.cc
src/vw.h
tests
tests/test1.r
tests/test2.r
tests/test5.r
tests/test6.r
tests/test7.r
tests/test8.r
RVowpalWabbit documentation built on May 21, 2017, 1:24 a.m.