Package: bigrf
Version: 0.1-5
Date: 2013-04-11
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"))
Author: Aloysius Lim, Leo Breiman, Adele Cutler
Maintainer: Aloysius Lim <aloysius.lim@gmail.com>
OS_type: unix
Depends: R (>= 2.14), methods, bigmemory, BH
Imports: foreach
LinkingTo: bigmemory, BH
Suggests: MASS, doParallel
Enhances: bigmemory
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 will be added in the future. See file
        INSTALL-WINDOWS in the source package for Windows installation
        instructions.
License: GPL-3
Copyright: 2013 Aloysius Lim
URL: https://github.com/aloysius-lim/bigrf
BugReports: https://github.com/aloysius-lim/bigrf/issues
Packaged: 2013-04-12 12:58:59 UTC; aloysius
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-04-12 18:04:00
