Package: fastAdaboost
Type: Package
Title: a Fast Implementation of Adaboost
Description: Implements Adaboost based on C++ backend code.
             This is blazingly fast and especially useful for large, in memory data sets. 
             The package uses decision trees as weak classifiers. Once the classifiers
             have been trained, they can be used to predict new data. 
             Currently, we support only binary classification tasks.
             The package implements the Adaboost.M1 algorithm and the real
             Adaboost(SAMME.R) algorithm.
Version: 1.0.0
Date: 2016-02-23
Author: Sourav Chatterjee [aut, cre]
Maintainer: Sourav Chatterjee <souravc83@gmail.com>
License: MIT + file LICENSE
URL: https://github.com/souravc83/fastAdaboost
BugReports: https://github.com/souravc83/fastAdaboost/issues
Depends: R (>= 3.1.2)
Imports: Rcpp, rpart
Suggests: testthat, knitr, MASS
LazyData: yes
LinkingTo: Rcpp (>= 0.12.0)
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-02-26 04:51:01 UTC; sourav
Repository: CRAN
Date/Publication: 2016-02-28 09:59:32
