From e04b6aaec54fb7abbbb3e9b11630baa4b022e275 Mon Sep 17 00:00:00 2001
From: hetong <hetong007@gmail.com>
Date: Sat, 6 Sep 2014 19:02:23 -0700
Subject: [PATCH] add documentation for datasets

---
 R-package/R/xgboost.R           | 55 +++++++++++++++++++++++++++++++++
 R-package/man/agaricus.train.Rd | 33 ++++++++++++++++++++
 R-package/man/xgb.cv.Rd         |  2 +-
 3 files changed, 89 insertions(+), 1 deletion(-)
 create mode 100644 R-package/man/agaricus.train.Rd

diff --git a/R-package/R/xgboost.R b/R-package/R/xgboost.R
index 24c50fec0..a08ca3fa8 100644
--- a/R-package/R/xgboost.R
+++ b/R-package/R/xgboost.R
@@ -53,3 +53,58 @@ xgboost <- function(data = NULL, label = NULL, params = list(), nrounds,
   
   return(bst)
 } 
+
+
+#' Training part from Mushroom Data Set
+#' 
+#' This data set is originally from the Mushroom data set,
+#' UCI Machine Learning Repository.
+#' 
+#' This data set includes the following fields:
+#' 
+#' \itemize{
+#'  \item \code{label} the label for each record
+#'  \item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
+#' }
+#'
+#'#' @references
+#' https://archive.ics.uci.edu/ml/datasets/Mushroom
+#' 
+#' Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository 
+#' [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, 
+#' School of Information and Computer Science.
+#' 
+#' @docType data
+#' @keywords datasets
+#' @name agaricus.train
+#' @usage data(agaricus.train)
+#' @format A list containing a label vector, and a dgCMatrix object with 6513 
+#' rows and 127 variables
+NULL
+
+#' Test part from Mushroom Data Set
+#'
+#' This data set is originally from the Mushroom data set,
+#' UCI Machine Learning Repository.
+#' 
+#' This data set includes the following fields:
+#' 
+#' \itemize{
+#'  \item \code{label} the label for each record
+#'  \item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
+#' }
+#'
+#' @references
+#' https://archive.ics.uci.edu/ml/datasets/Mushroom
+#' 
+#' Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository 
+#' [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, 
+#' School of Information and Computer Science.
+#' 
+#' @docType data
+#' @keywords datasets
+#' @name agaricus.test
+#' @usage data(agaricus.test)
+#' @format A list containing a label vector, and a dgCMatrix object with 1611 
+#' rows and 127 variables
+NULL
diff --git a/R-package/man/agaricus.train.Rd b/R-package/man/agaricus.train.Rd
new file mode 100644
index 000000000..d1a401ecd
--- /dev/null
+++ b/R-package/man/agaricus.train.Rd
@@ -0,0 +1,33 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
+\docType{data}
+\name{agaricus.train}
+\alias{agaricus.train}
+\title{Training part from Mushroom Data Set}
+\format{A list containing a label vector, and a dgCMatrix object with 6513
+rows and 127 variables}
+\usage{
+data(agaricus.train)
+}
+\description{
+This data set is originally from the Mushroom data set,
+UCI Machine Learning Repository.
+}
+\details{
+This data set includes the following fields:
+
+\itemize{
+ \item \code{label} the label for each record
+ \item \code{data} a sparse Matrix of \code{dgCMatrix} class, with 127 rows.
+}
+
+#'
+}
+\references{
+https://archive.ics.uci.edu/ml/datasets/Mushroom
+
+Bache, K. & Lichman, M. (2013). UCI Machine Learning Repository
+[http://archive.ics.uci.edu/ml]. Irvine, CA: University of California,
+School of Information and Computer Science.
+}
+\keyword{datasets}
+
diff --git a/R-package/man/xgb.cv.Rd b/R-package/man/xgb.cv.Rd
index 10ee6f5f0..b7fa677f9 100644
--- a/R-package/man/xgb.cv.Rd
+++ b/R-package/man/xgb.cv.Rd
@@ -30,7 +30,7 @@ xgb.cv(params = list(), data, nrounds, nfold, label = NULL, showsd = TRUE,
 
 \item{label}{option field, when data is Matrix}
 
-\item{showd}{boolean, whether show standard deviation of cross validation}
+\item{showsd}{boolean, whether show standard deviation of cross validation}
 
 \item{metrics,}{list of evaluation metrics to be used in corss validation,
   when it is not specified, the evaluation metric is chosen according to objective function.