Load xgboost model from binary file
Load xgboost model from the binary model file.
xgb.load(modelfile)
modelfile |
the name of the binary input file. |
The input file is expected to contain a model saved in an xgboost-internal binary format
using either xgb.save or cb.save.model 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 xgb.load.
An object of xgb.Booster class.
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.