Merge 3a66798 into 12dfc96

pkg/caret/inst/NEWS.Rd

@@ -20,6 +20,7 @@
 		\item The model-specific code for computing out-of-bag performance estimates were moved into the model code library \issue{230}.
 		\item A variety of naive Bayes and tree augmented naive Bayes classifier from the \cpkg{bnclassify} package were added. Variations include simple models (methods labeled as \code{"nbDiscrete"} and \code{"tan"}), models using attribute weighting (\code{"awnb"} and \code{"awtan"}), and wrappers that use search methods to optimize the network structure (\code{"nbSearch"} and \code{"tanSearch"}). In each case, the predictors and outcomes must all be factor variables; for that reason, using the non-formula interface to \code{train} (e.g. \code{train(x, y)}) is critical to preserve the factor structure of the data.  
 	} 
+		\item \code{xgboost} package that contains models \code{xgbTree} and \code{xgbLinear} is now being installed from CRAN. 
 }
 
 

release_process/update_pkgs.R

@@ -23,7 +23,7 @@ libs <- c(libs, "knitr", "Hmisc", "googleVis", "animation",
           "desirability", "gsubfn", "gtools", "impute", "Matrix", "proxy", "plyr", 
           "reshape", "rJava", "SparseM", "sqldf", "XML", "lubridate", "dplyr", "GA",
           "aroma.affymetrix", "remMap", "cghFLasso", "RCurl", "QSARdata", "reshape2",
-          "mapproj", "ggmap", "ggvis", "SuperLearner", "subsemble", "caretEnsemble")
+          "mapproj", "ggmap", "ggvis", "SuperLearner", "subsemble", "caretEnsemble", "xgboost")
 libs <- unique(libs)
 
 
@@ -39,8 +39,6 @@ if(length(diffs) > 0) print(diffs)
 ###################################################################
 ## Install the files. This might re-install caret so beware.
 
-devtools::install_github('dmlc/xgboost',subdir='R-package')
-
 install.packages(libs, repos = "http://cran.r-project.org", 
                  type = "source",
                  dependencies = c("Depends", "Suggests", "Imports"))