% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xgb.save.R
\name{xgb.save}
\alias{xgb.save}
\title{Save xgboost model to binary file}
\usage{
xgb.save(model, fname)
}
\arguments{
\item{model}{model object of \code{xgb.Booster} class.}

\item{fname}{name of the file to write.}
}
\description{
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
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
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. 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,
               eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
xgb.save(bst, 'xgb.model')
bst <- xgb.load('xgb.model')
if (file.exists('xgb.model')) file.remove('xgb.model')
pred <- predict(bst, test$data)
}
\seealso{
\code{\link{xgb.load}}, \code{\link{xgb.Booster.complete}}.
}