Load XGBoost model from binary model 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()
.
Examples
DONTSHOW({RhpcBLASctl::omp_set_num_threads(1)})
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)