From ee9d6e1533070c63cd21d5a2f67799415d328845 Mon Sep 17 00:00:00 2001
From: Suraj Yerramilli
Date: Fri, 6 Feb 2015 22:46:27 +0530
Subject: added an example to documentation

---
 R/partition.R        | 7 +++++++
 man/dataPartition.Rd | 6 ++++++
 2 files changed, 13 insertions(+)

diff --git a/R/partition.R b/R/partition.R
index ab9dba6..0c92e76 100644
--- a/R/partition.R
+++ b/R/partition.R
@@ -35,6 +35,13 @@ dataSlice <- function(object,indices){
 #' @param object an object of class \code{idframe}
 #' @param p the percentage of the data that goes to training (Default : \code{0.6})
 #' @return list containing estimation and validation idframe objects
+#' 
+#' @examples
+#' data(cstr)
+#' splitList <- dataPartition(cstr,p=0.6)
+#' train <- splitList$estimation # training set 
+#' test <- splitList$validation # testing set
+#' 
 #' @export
 dataPartition <- function(object,p=0.6){
   # check if the class is correct
diff --git a/man/dataPartition.Rd b/man/dataPartition.Rd
index 501ace2..afcc473 100644
--- a/man/dataPartition.Rd
+++ b/man/dataPartition.Rd
@@ -18,4 +18,10 @@ list containing estimation and validation idframe objects
 The function splits the data into training and validation sets and returns them bundled
 as a list. The size of the sets are determined by the parameter \code{p}.
 }
+\examples{
+data(cstr)
+splitList <- dataPartition(cstr,p=0.6)
+train <- splitList$estimation # training set
+test <- splitList$validation # testing set
+}
 
-- 
cgit