46 lines
1.7 KiB
R
46 lines
1.7 KiB
R
% Generated by roxygen2 (4.1.0): do not edit by hand
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% Please edit documentation in R/xgb.dump.R
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\name{xgb.dump}
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\alias{xgb.dump}
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\title{Save xgboost model to text file}
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\usage{
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xgb.dump(model = NULL, fname = NULL, fmap = "", with.stats = FALSE)
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}
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\arguments{
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\item{model}{the model object.}
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\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.}
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\item{fmap}{feature map file representing the type of feature.
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Detailed description could be found at
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\url{https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model}.
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See demo/ for walkthrough example in R, and
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\url{https://github.com/tqchen/xgboost/blob/master/demo/data/featmap.txt}
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for example Format.}
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\item{with.stats}{whether dump statistics of splits
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When this option is on, the model dump comes with two additional statistics:
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gain is the approximate loss function gain we get in each split;
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cover is the sum of second order gradient in each node.}
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}
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\value{
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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}.
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}
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\description{
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Save a xgboost model to text file. Could be parsed later.
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}
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\examples{
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data(agaricus.train, package='xgboost')
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data(agaricus.test, package='xgboost')
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train <- agaricus.train
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test <- agaricus.test
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bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
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eta = 1, nround = 2,objective = "binary:logistic")
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# save the model in file 'xgb.model.dump'
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xgb.dump(bst, 'xgb.model.dump', with.stats = T)
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# print the model without saving it to a file
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print(xgb.dump(bst))
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}
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