xgb.load: Load XGBoost model from binary file

In xgboost: Extreme Gradient Boosting

Load XGBoost model from binary file

Description

Load XGBoost model from binary model file.

Usage

xgb.load(modelfile)

Arguments

modelfile

The name of the binary input file.

Details

The input file is expected to contain a model saved in an XGBoost model format using either xgb.save() in R, or using some appropriate methods from other XGBoost interfaces. E.g., a model trained in Python and saved from there in XGBoost format, could be loaded from R.

Note: a model saved as an R object has to be loaded using corresponding R-methods, not by xgb.load().

Value

An object of xgb.Booster class.

See Also

xgb.save()

Examples

data(agaricus.train, package = "xgboost")
data(agaricus.test, package = "xgboost")

## Keep the number of threads to 1 for examples
nthread <- 1
data.table::setDTthreads(nthread)

train <- agaricus.train
test <- agaricus.test

bst <- xgb.train(
  data = xgb.DMatrix(train$data, label = train$label, nthread = 1),
  nrounds = 2,
  params = xgb.params(
    max_depth = 2,
    nthread = nthread,
    objective = "binary:logistic"
  )
)

fname <- file.path(tempdir(), "xgb.ubj")
xgb.save(bst, fname)
bst <- xgb.load(fname)

xgboost documentation built on Dec. 3, 2025, 5:06 p.m.