From a524a51a06f979e5ea4d6a14e5c6368c88549dd0 Mon Sep 17 00:00:00 2001
From: El Potaeto <pommedeterresautee@msn.com>
Date: Thu, 1 Jan 2015 16:05:43 +0100
Subject: [PATCH] return history as data.table for cross validation +
 documentation

---
 R-package/NAMESPACE     |  1 +
 R-package/R/xgb.cv.R    | 23 ++++++++++++++++++-----
 R-package/man/xgb.cv.Rd |  3 +++
 3 files changed, 22 insertions(+), 5 deletions(-)

diff --git a/R-package/NAMESPACE b/R-package/NAMESPACE
index 1714d2044..7e0bfa8ac 100644
--- a/R-package/NAMESPACE
+++ b/R-package/NAMESPACE
@@ -18,5 +18,6 @@ importClassesFrom(Matrix,dgCMatrix)
 importClassesFrom(Matrix,dgeMatrix)
 importFrom(data.table,":=")
 importFrom(data.table,data.table)
+importFrom(data.table,rbindlist)
 importFrom(magrittr,"%>%")
 importFrom(stringr,str_extract)
diff --git a/R-package/R/xgb.cv.R b/R-package/R/xgb.cv.R
index 02870b772..3a9fd9b86 100644
--- a/R-package/R/xgb.cv.R
+++ b/R-package/R/xgb.cv.R
@@ -1,7 +1,12 @@
 #' Cross Validation
 #' 
 #' The cross valudation function of xgboost
-#'
+#' 
+#' @importFrom data.table data.table
+#' @importFrom magrittr %>%
+#' @importFrom data.table :=
+#' @importFrom data.table rbindlist
+#' @importFrom stringr str_extract
 #' @param params the list of parameters. Commonly used ones are:
 #' \itemize{
 #'   \item \code{objective} objective function, common ones are
@@ -40,6 +45,8 @@
 #     value that represents missing value. Sometime a data use 0 or other extreme value to represents missing values.
 #' @param ... other parameters to pass to \code{params}.
 #' 
+#' @return a \code{data.table} with each mean and standard deviation stat for training set and test set.
+#' 
 #' @details 
 #' This is the cross validation function for xgboost
 #'
@@ -88,9 +95,15 @@ xgb.cv <- function(params=list(), data, nrounds, nfold, label = NULL, missing =
     history <- c(history, ret)
     cat(paste(ret, "\n", sep=""))
   }
-  return (history)
+  
+  dt <- data.table(train_rmse_mean=numeric(), train_rmse_std=numeric(), train_auc_mean=numeric(), train_auc_std=numeric(), test_rmse_mean=numeric(), test_rmse_std=numeric(), test_auc_mean=numeric(), test_auc_std=numeric())
+  
+  split = str_split(string = history, pattern = "\t")
+  for(line in split){
+    dt <- line[2:length(line)] %>% str_extract_all(pattern = "\\d.\\d*") %>% unlist %>% as.list %>% {vec <- .;rbindlist(list(dt, vec), use.names = F, fill = F)}
+  }
+  dt
 }
 
-xgb.cv.strip.numeric <- function(x) {
-  as.numeric(strsplit(regmatches(x, regexec("test-(.*):(.*)$", x))[[1]][3], "\\+")[[1]])
-}
+
+
diff --git a/R-package/man/xgb.cv.Rd b/R-package/man/xgb.cv.Rd
index 271182625..19f04ee79 100644
--- a/R-package/man/xgb.cv.Rd
+++ b/R-package/man/xgb.cv.Rd
@@ -56,6 +56,9 @@ prediction and dtrain,}
 
 \item{...}{other parameters to pass to \code{params}.}
 }
+\value{
+a \code{data.table} with each mean and standard deviation stat for training set and test set.
+}
 \description{
 The cross valudation function of xgboost
 }