R: Load xgboost model from binary file

xgb.load {xgboost} | R Documentation

## Load xgboost model from binary file

### Description

Load xgboost model from the 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-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`.

### Value

An object of `xgb.Booster` class.

### See Also

`xgb.save`, `xgb.Booster.complete`.

### 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)

[Package xgboost version 1.4.2.1 Index]