add basic walkthrough

R-package/R/xgb.train.R

@@ -29,6 +29,9 @@
 #' @param feval custimized evaluation function. Returns 
 #'   \code{list(metric='metric-name', value='metric-value')} with given 
 #'   prediction and dtrain,
+#' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print 
+#'   information of performance. If 2, xgboost will print information of both
+#'
 #' @param ... other parameters to pass to \code{params}.
 #' 
 #' @details 
@@ -65,7 +68,7 @@
 #' @export
 #' 
 xgb.train <- function(params=list(), data, nrounds, watchlist = list(), 
-                      obj = NULL, feval = NULL, ...) {
+                      obj = NULL, feval = NULL, verbose = 1, ...) {
   dtrain <- data
   if (typeof(params) != "list") {
     stop("xgb.train: first argument params must be list")
@@ -73,7 +76,17 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
   if (class(dtrain) != "xgb.DMatrix") {
     stop("xgb.train: second argument dtrain must be xgb.DMatrix")
   }
+  if (verbose > 1) {
+    params <- append(params, list(silent = 0))
+  } else {
+    params <- append(params, list(silent = 1))
+  }
+  if (length(watchlist) != 0 && verbose == 0) {
+    warning('watchlist is provided but verbose=0, no evaluation information will be printed')
+    watchlist <- list()
+  }
   params = append(params, list(...))
+  
   bst <- xgb.Booster(params, append(watchlist, dtrain))
   for (i in 1:nrounds) {
     succ <- xgb.iter.update(bst, dtrain, i - 1, obj)

R-package/R/xgboost.R

@@ -40,14 +40,7 @@
 #' 
 xgboost <- function(data = NULL, label = NULL, params = list(), nrounds, 
                     verbose = 1, ...) {
-  dtrain <- xgb.get.DMatrix(data, label)
-  if (verbose > 1) {
-    silent <- 0 
-  } else {
-    silent <- 1
-  }
-  
-  params <- append(params, list(silent = silent))
+  dtrain <- xgb.get.DMatrix(data, label)  
   params <- append(params, list(...))
   
   if (verbose > 0) {
@@ -56,7 +49,7 @@ xgboost <- function(data = NULL, label = NULL, params = list(), nrounds,
     watchlist <- list()
   }
   
-  bst <- xgb.train(params, dtrain, nrounds, watchlist)
+  bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose=verbose)
   
   return(bst)
 }