Dump an xgboost model in text format.
Dump an xgboost model in text format.
xgb.dump(
model,
fname = NULL,
fmap = "",
with_stats = FALSE,
dump_format = c("text", "json"),
...
)model |
the model object. |
fname |
the name of the text file where to save the model text dump.
If not provided or set to |
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 |
If fname is not provided or set to NULL the function will return the model
as a character vector. Otherwise it will return TRUE.
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'))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.