compile Rd files, i.e. R documents

R-package/R/getinfo.xgb.DMatrix.R

@@ -7,9 +7,6 @@ setClass('xgb.DMatrix')
 #' @param object Object of class "xgb.DMatrix"
 #' @param name the name of the field to get
 #' 
-#' @section Value
-#' return a numerical vector.
-#' 
 #' @examples
 #' data(iris)
 #' iris[,5] <- as.numeric(iris[,5])

R-package/R/predict.xgb.Booster.R

@@ -11,9 +11,6 @@ setClass("xgb.Booster")
 #'   value of sum of functions, when outputmargin=TRUE, the prediction is 
 #'   untransformed margin value. In logistic regression, outputmargin=T will
 #'   output value before logistic transformation.
-#'
-#' @section Value
-#' return a numerical vector.
 #' 
 #' @examples
 #' data(iris)

R-package/R/xgb.train.R

@@ -36,8 +36,6 @@
 #' It supports advanced features such as watchlist, customized objective function,
 #' therefore it is more flexible than \code{\link{xgboost}}.
 #' 
-#' @section Value
-#' return a \code{xgb.DMatrix} class object.
 #' 
 #' @examples
 #' data(iris)

R-package/R/xgboost.R

@@ -28,9 +28,6 @@
 #' Parallelization is automatically enabled if OpenMP is present.
 #' Number of threads can also be manually specified via "nthread" parameter
 #' 
-#' @section Value
-#' return a \code{xgb.DMatrix} class object.
-#' 
 #' @examples
 #' data(iris)
 #' bst <- xgboost(as.matrix(iris[,1:4]),as.numeric(iris[,5]), nrounds = 2)