xgb.dump
Dump an xgboost model in text format.
Dump an xgboost model in text format.
Usage
xgb.dump(model, fname = NULL, fmap = "", with_stats = FALSE,
dump_format = c("text", "json"), ...)Arguments
- model
the model object.
- fname
the name of the text file where to save the model text dump. If not provided or set to
NULL, the model is returned as acharactervector.- fmap
feature map file representing feature types. Detailed description could be found at https://github.com/dmlc/xgboost/wiki/Binary-Classification#dump-model. See demo/ for walkthrough example in R, and https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt for example Format.
- with_stats
whether to dump some additional statistics about the splits. When this option is on, the model dump contains two additional values: gain is the approximate loss function gain we get in each split; cover is the sum of second order gradient in each node.
- dump_format
either 'text' or 'json' format could be specified.
- ...
currently not used
Value
If fname is not provided or set to NULL the function will return the model
as a character vector. Otherwise it will return TRUE.
Examples
# NOT RUN {
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")
# save the model in file 'xgb.model.dump'
dump_path = file.path(tempdir(), 'model.dump')
xgb.dump(bst, dump_path, with_stats = TRUE)
# print the model without saving it to a file
print(xgb.dump(bst, with_stats = TRUE))
# print in JSON format:
cat(xgb.dump(bst, with_stats = TRUE, dump_format='json'))
# }