xgboost/R-package/man/xgb.dump.Rd
Vadim Khotilovich a375ad2822 [R] maintenance Apr 2017 (#2237)
* [R] make sure things work for a single split model; fixes #2191

* [R] add option use_int_id to xgb.model.dt.tree

* [R] add example of exporting tree plot to a file

* [R] set save_period = NULL as default in xgboost() to be the same as in xgb.train; fixes #2182

* [R] it's a good practice after CRAN releases to bump up package version in dev

* [R] allow xgb.DMatrix construction from integer dense matrices

* [R] xgb.DMatrix: silent parameter; improve documentation

* [R] xgb.model.dt.tree code style changes

* [R] update NEWS with parameter changes

* [R] code safety & style; handle non-strict matrix and inherited classes of input and model; fixes #2242

* [R] change to x.y.z.p R-package versioning scheme and set version to 0.6.4.3

* [R] add an R package versioning section to the contributors guide

* [R] R-package/README.md: clean up the redundant old installation instructions, link the contributors guide
2017-05-01 22:51:34 -07:00

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R

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/xgb.dump.R
\name{xgb.dump}
\alias{xgb.dump}
\title{Dump an xgboost model in text format.}
\usage{
xgb.dump(model, fname = NULL, fmap = "", with_stats = FALSE,
dump_format = c("text", "json"), ...)
}
\arguments{
\item{model}{the model object.}
\item{fname}{the name of the text file where to save the model text dump.
If not provided or set to \code{NULL}, the model is returned as a \code{character} vector.}
\item{fmap}{feature map file representing feature types.
Detailed description could be found at
\url{https://github.com/dmlc/xgboost/wiki/Binary-Classification#dump-model}.
See demo/ for walkthrough example in R, and
\url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt}
for example Format.}
\item{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.}
\item{dump_format}{either 'text' or 'json' format could be specified.}
\item{...}{currently not used}
}
\value{
If fname is not provided or set to \code{NULL} the function will return the model
as a \code{character} vector. Otherwise it will return \code{TRUE}.
}
\description{
Dump an xgboost model in text format.
}
\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")
# save the model in file 'xgb.model.dump'
xgb.dump(bst, 'xgb.model.dump', 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'))
}