refine doc, with Rd

R-package/man/xgb.cv.Rd

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+% Generated by roxygen2 (4.0.1): do not edit by hand
+\name{xgb.cv}
+\alias{xgb.cv}
+\title{Cross Validation}
+\usage{
+xgb.cv(params = list(), data, nrounds, nfold, label = NULL, showsd = TRUE,
+  metrics = list(), obj = NULL, feval = NULL, ...)
+}
+\arguments{
+\item{params}{the list of parameters. Commonly used ones are:
+\itemize{
+  \item \code{objective} objective function, common ones are
+  \itemize{
+    \item \code{reg:linear} linear regression
+    \item \code{binary:logistic} logistic regression for classification
+  }
+  \item \code{eta} step size of each boosting step
+  \item \code{max_depth} maximum depth of the tree
+  \item \code{nthread} number of thread used in training, if not set, all threads are used
+}
+
+  See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for
+  further details. See also inst/examples/demo.R for walkthrough example in R.}
+
+\item{data}{takes an \code{xgb.DMatrix} as the input.}
+
+\item{nrounds}{the max number of iterations}
+
+\item{nfold}{number of folds used}
+
+\item{label}{option field, when data is Matrix}
+
+\item{showd}{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.
+  Possible options are:
+\itemize{
+  \item \code{error} binary classification error rate
+  \item \code{rmse} Rooted mean square error
+  \item \code{logloss} negative log-likelihood function
+  \item \code{auc} Area under curve
+  \item \code{merror} Exact matching error, used to evaluate multi-class classification
+}}
+
+\item{obj}{customized objective function. Returns gradient and second order
+gradient with given prediction and dtrain,}
+
+\item{feval}{custimized evaluation function. Returns
+\code{list(metric='metric-name', value='metric-value')} with given
+prediction and dtrain,}
+
+\item{...}{other parameters to pass to \code{params}.}
+}
+\description{
+The cross valudation function of xgboost
+}
+\details{
+This is the cross validation function for xgboost
+
+Parallelization is automatically enabled if OpenMP is present.
+Number of threads can also be manually specified via "nthread" parameter.
+
+This function only accepts an \code{xgb.DMatrix} object as the input.
+}
+