DESCRIPTION

Package: bigrf
Version: 0.1-12
Date: 2015-10-21
Title: Big Random Forests: Classification and Regression Forests for Large Data Sets
Authors@R: c(person("Aloysius", "Lim", role = c("aut", "cre"),
                    email="aloysius.lim@gmail.com"),
             person("Leo", "Breiman", role = "aut"),
             person("Adele", "Cutler", role = "aut"))
Maintainer: Aloysius Lim <aloysius.lim@gmail.com>
OS_type: unix
Depends: R (>= 2.14), methods, bigmemory (>= 4.5.8)
Imports: foreach
Suggests: MASS, doParallel
LinkingTo: bigmemory, BH
Description: This is an implementation of Leo Breiman's and Adele Cutler's
  Random Forest algorithms for classification and regression, with optimizations
  for performance and for handling of data sets that are too large to be
  processed in memory. Forests can be built in parallel at two levels. First,
  trees can be grown in parallel on a single machine using foreach. Second,
  multiple forests can be built in parallel on multiple machines, then merged
  into one. For large data sets, disk-based big.matrix's may be used for storing
  data and intermediate computations, to prevent excessive virtual memory
  swapping by the operating system. Currently, only classification forests with
  a subset of the functionality in Breiman and Cutler's original code are
  implemented. More functionality and regression trees may be added in the
  future.
License: GPL-3
Copyright: 2013-2015 Aloysius Lim
URL: https://github.com/aloysius-lim/bigrf
BugReports: https://github.com/aloysius-lim/bigrf/issues