Update R doc by roxygen2. (#5201)
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@@ -4,11 +4,28 @@
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\alias{xgb.cv}
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\title{Cross Validation}
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\usage{
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xgb.cv(params = list(), data, nrounds, nfold, label = NULL, missing = NA,
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prediction = FALSE, showsd = TRUE, metrics = list(), obj = NULL,
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feval = NULL, stratified = TRUE, folds = NULL, verbose = TRUE,
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print_every_n = 1L, early_stopping_rounds = NULL, maximize = NULL,
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callbacks = list(), ...)
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xgb.cv(
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params = list(),
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data,
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nrounds,
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nfold,
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label = NULL,
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missing = NA,
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prediction = FALSE,
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showsd = TRUE,
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metrics = list(),
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obj = NULL,
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feval = NULL,
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stratified = TRUE,
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folds = NULL,
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train_folds = NULL,
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verbose = TRUE,
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print_every_n = 1L,
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early_stopping_rounds = NULL,
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maximize = NULL,
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callbacks = list(),
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...
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)
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}
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\arguments{
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\item{params}{the list of parameters. Commonly used ones are:
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@@ -69,6 +86,9 @@ by the values of outcome labels.}
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(each element must be a vector of test fold's indices). When folds are supplied,
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the \code{nfold} and \code{stratified} parameters are ignored.}
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\item{train_folds}{\code{list} list specifying which indicies to use for training. If \code{NULL}
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(the default) all indices not specified in \code{folds} will be used for training.}
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\item{verbose}{\code{boolean}, print the statistics during the process}
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\item{print_every_n}{Print each n-th iteration evaluation messages when \code{verbose>0}.
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