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[R] Provide better guidance for persisting XGBoost model (#5964)

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* [R] Provide better guidance for persisting XGBoost model

* Update saving_model.rst

* Add a paragraph about xgb.serialize()
This commit is contained in:
Philip Hyunsu Cho
2020-07-31 20:00:26 -07:00
committed by GitHub
parent bf2990e773
commit 5a2dcd1c33
17 changed files with 233 additions and 82 deletions
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16
R-package/man/xgb.save.Rd
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@@ -15,21 +15,25 @@ xgb.save(model, fname)
Save xgboost model to a file in binary format.
}
\details{
This methods allows to save a model in an xgboost-internal binary format which is universal
This methods allows to save a model in an xgboost-internal binary format which is universal
among the various xgboost interfaces. In R, the saved model file could be read-in later
using either the \code{\link{xgb.load}} function or the \code{xgb_model} parameter
using either the \code{\link{xgb.load}} function or the \code{xgb_model} parameter
of \code{\link{xgb.train}}.
Note: a model can also be saved as an R-object (e.g., by using \code{\link[base]{readRDS}}
or \code{\link[base]{save}}). However, it would then only be compatible with R, and
corresponding R-methods would need to be used to load it.
Note: a model can also be saved as an R-object (e.g., by using \code{\link[base]{readRDS}}
or \code{\link[base]{save}}). However, it would then only be compatible with R, and
corresponding R-methods would need to be used to load it. Moreover, persisting the model with
\code{\link[base]{readRDS}} or \code{\link[base]{save}}) will cause compatibility problems in
future versions of XGBoost. Consult \code{\link{a-compatibility-note-for-saveRDS-save}} to learn
how to persist models in a future-proof way, i.e. to make the model accessible in future
releases of XGBoost.
}
\examples{
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, nrounds = 2,objective = "binary:logistic")
xgb.save(bst, 'xgb.model')
bst <- xgb.load('xgb.model')