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Update lib version dependencies (for DiagrammeR mainly)

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Fix @export tag in each R file (for Roxygen 5, otherwise it doesn't work anymore)
Regerate Roxygen doc
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2015-11-07 21:01:28 +01:00
parent 635645c650
commit 0052b193cf
36 changed files with 123 additions and 126 deletions
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18
R-package/man/xgb.dump.Rd
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@@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xgb.dump.R
\name{xgb.dump}
\alias{xgb.dump}
@@ -11,17 +11,17 @@ xgb.dump(model = NULL, fname = NULL, fmap = "", with.stats = FALSE)
\item{fname}{the name of the text file where to save the model text dump. If not provided or set to \code{NULL} the function will return the model as a \code{character} vector.}
\item{fmap}{feature map file representing the type of feature.
Detailed description could be found at
\item{fmap}{feature map file representing the type of feature.
Detailed description could be found at
\url{https://github.com/dmlc/xgboost/wiki/Binary-Classification#dump-model}.
See demo/ for walkthrough example in R, and
\url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt}
\url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt}
for example Format.}
\item{with.stats}{whether dump statistics of splits
When this option is on, the model dump comes with two additional statistics:
gain is the approximate loss function gain we get in each split;
cover is the sum of second order gradient in each node.}
\item{with.stats}{whether dump statistics of splits
When this option is on, the model dump comes with two additional statistics:
gain is the approximate loss function gain we get in each split;
cover is the sum of second order gradient in each node.}
}
\value{
if fname is not provided or set to \code{NULL} the function will return the model as a \code{character} vector. Otherwise it will return \code{TRUE}.
@@ -34,7 +34,7 @@ data(agaricus.train, package='xgboost')
data(agaricus.test, package='xgboost')
train <- agaricus.train
test <- agaricus.test
bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
eta = 1, nthread = 2, nround = 2,objective = "binary:logistic")
# save the model in file 'xgb.model.dump'
xgb.dump(bst, 'xgb.model.dump', with.stats = TRUE)