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

Description

The vw function applies the Vowpal Wabbit on-line learner to a given data set and model.

Vowpal Wabbit is a project sponsored by Yahoo! Research and led by John Langford.

At present, this package provides a simple yet crude interface.

Usage

vw(args, quiet=TRUE)

Arguments

args

A character vector containing the same arguments one would use on the command-line with the standalone vw binary.

quiet

A boolean switch which, if set, suppresses most output to stdout.

Value

The vw returns a small data.frame with a number of summary statistics function returns a character string of a fixed length containing the requested digest of the supplied R object. For MD5, a string of length 32 is returned; for SHA-1, a string of length 40 is returned; for CRC32 a string of length 8.

Details

Vowpal Wabbit is a very fast on-line machine learning application. Some documentation for it is provided via the upstream wiki referenced below.

References

https://github.com/JohnLangford/vowpal_wabbit/wiki

Examples

Run this code

# NOT RUN {
  ## also see demo(vw) from which this is a subset

  library(RVowpalWabbit)

  # Test 3: without -d, training only
  # {VW} train-sets/0002.dat    -f models/0002.model
  test3 <- c("-t", system.file("test", "train-sets", "0002.dat", package="RVowpalWabbit"),
             "-f", file.path(tempdir(), "0002.model"),
             "--cache_file", file.path(tempdir(), "0002.cache"))

  res <- vw(test3)
  res
# }

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