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attemp to fix line breaking issue of doc

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hetong 2014-09-01 17:43:28 -07:00
parent 19887dcc37
commit 76d5fc7e78
4 changed files with 21 additions and 14 deletions
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9
R-package/R/xgb.dump.R
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@ -4,9 +4,12 @@
#' #'
#' @param model the model object. #' @param model the model object.
#' @param fname the name of the binary file. #' @param fname the name of the binary file.
#' @param fmap feature map file representing the type of feature, to make it #' @param fmap feature map file representing the type of feature.
#' look nice, run inst/examples/demo.R for result and inst/examples/featmap.txt for example #' Detailed description could be found at
#' Format: https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model #' \url{https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model}.
#' Run inst/examples/demo.R for the result and inst/examples/featmap.txt
#' for example Format.
#'
#' #'
#' @examples #' @examples
#' data(iris) #' data(iris)

9
R-package/R/xgb.train.R
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@ -24,10 +24,11 @@
#' watchlist=list(validation1=mat1, validation2=mat2) to watch #' watchlist=list(validation1=mat1, validation2=mat2) to watch
#' the performance of each round's model on mat1 and mat2 #' the performance of each round's model on mat1 and mat2
#' #'
#' @param obj customized objective function. Given prediction and dtrain, #' @param obj customized objective function. Returns gradient and second order
#' return gradient and second order gradient. #' gradient with given prediction and dtrain,
#' @param feval custimized evaluation function. Given prediction and dtrain, #' @param feval custimized evaluation function. Returns
#' return a \code{list(metric='metric-name', value='metric-value')}. #' \code{list(metric='metric-name', value='metric-value')} with given
#' prediction and dtrain,
#' @param ... other parameters to pass to \code{params}. #' @param ... other parameters to pass to \code{params}.
#' #'
#' @details #' @details

8
R-package/man/xgb.dump.Rd
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@ -10,9 +10,11 @@ xgb.dump(model, fname, fmap = "")
\item{fname}{the name of the binary file.} \item{fname}{the name of the binary file.}
\item{fmap}{feature map file representing the type of feature, to make it \item{fmap}{feature map file representing the type of feature.
look nice, run inst/examples/demo.R for result and inst/examples/featmap.txt for example Detailed description could be found at
Format: https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model} \url{https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model}.
Run inst/examples/demo.R for the result and inst/examples/featmap.txt
for example Format.}
} }
\description{ \description{
Save a xgboost model to text file. Could be parsed later. Save a xgboost model to text file. Could be parsed later.

9
R-package/man/xgb.train.Rd
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@ -32,11 +32,12 @@ xgb.train(params = list(), dtrain, nrounds, watchlist = list(),
watchlist=list(validation1=mat1, validation2=mat2) to watch watchlist=list(validation1=mat1, validation2=mat2) to watch
the performance of each round's model on mat1 and mat2} the performance of each round's model on mat1 and mat2}
\item{obj}{customized objective function. Given prediction and dtrain, \item{obj}{customized objective function. Returns gradient and second order
return gradient and second order gradient.} gradient with given prediction and dtrain,}
\item{feval}{custimized evaluation function. Given prediction and dtrain, \item{feval}{custimized evaluation function. Returns
return a \code{list(metric='metric-name', value='metric-value')}.} \code{list(metric='metric-name', value='metric-value')} with given
prediction and dtrain,}
\item{...}{other parameters to pass to \code{params}.} \item{...}{other parameters to pass to \code{params}.}
} }