refine doc, with Rd

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

@@ -8,7 +8,10 @@ setClass('xgb.DMatrix')
 #' data(iris)
 #' iris[,5] <- as.numeric(iris[,5]=='setosa')
 #' dtrain <- xgb.DMatrix(as.matrix(iris[,1:4]), label=iris[,5])
-#' labels <- getinfo(dtrain, "label")
+#' labels <- getinfo(dtrain, 'label')
+#' setinfo(dtrain, 'label', 1-labels)
+#' labels2 <- getinfo(dtrain, 'label')
+#' stopifnot(all(labels2 == 1-labels))
 #' @rdname getinfo
 #' @export
 #' 

R-package/R/setinfo.xgb.DMatrix.R

@@ -6,7 +6,10 @@
 #' data(iris)
 #' iris[,5] <- as.numeric(iris[,5]=='setosa')
 #' dtrain <- xgb.DMatrix(as.matrix(iris[,1:4]), label=iris[,5])
-#' labels <- getinfo(dtrain, "label")
+#' labels <- getinfo(dtrain, 'label')
+#' setinfo(dtrain, 'label', 1-labels)
+#' labels2 <- getinfo(dtrain, 'label')
+#' stopifnot(all(labels2 == 1-labels))
 #' @rdname setinfo
 #' @export
 #' 
@@ -16,9 +19,10 @@ setinfo <- function(object, ...){
 
 #' @param object Object of class "xgb.DMatrix"
 #' @param name the name of the field to get
+#' @param info the specific field of information to set
 #' @param ... other parameters
-#' @rdname getinfo
-#' @method getinfo xgb.DMatrix
+#' @rdname setinfo
+#' @method setinfo xgb.DMatrix
 setMethod("setinfo", signature = "xgb.DMatrix", 
           definition = function(object, name, info) {
             xgb.setinfo(object, name, info)

R-package/R/xgb.cv.R

@@ -1,6 +1,6 @@
-#' eXtreme Gradient Boosting Training
+#' Cross Validation
 #' 
-#' The training function of xgboost
+#' The cross valudation function of xgboost
 #'
 #' @param params the list of parameters. Commonly used ones are:
 #' \itemize{
@@ -61,7 +61,7 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL,
   params <- append(params, list(silent=1))
   for (mc in metrics) {
     params <- append(params, list("eval_metric"=mc))
-  }    
+  }
 
   folds <- xgb.cv.mknfold(dtrain, nfold, params)
   history <- list()
@@ -70,7 +70,8 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL,
     for (k in 1:nfold) {
       fd <- folds[[k]]
       succ <- xgb.iter.update(fd$booster, fd$dtrain, i - 1, obj)      
-      msg[[k]] <- strsplit(xgb.iter.eval(fd$booster, fd$watchlist, i - 1, feval), "\t")[[1]]
+      msg[[k]] <- strsplit(xgb.iter.eval(fd$booster, fd$watchlist, i - 1, feval), 
+                           "\t")[[1]]
     }
     ret <- xgb.cv.aggcv(msg, showsd)
     history <- append(history, ret)