39 lines
1.3 KiB
R
39 lines
1.3 KiB
R
% Generated by roxygen2 (4.1.0): do not edit by hand
|
|
% Please edit documentation in R/xgb.dump.R
|
|
\name{xgb.dump}
|
|
\alias{xgb.dump}
|
|
\title{Save xgboost model to text file}
|
|
\usage{
|
|
xgb.dump(model, fname, fmap = "", with.stats = FALSE)
|
|
}
|
|
\arguments{
|
|
\item{model}{the model object.}
|
|
|
|
\item{fname}{the name of the binary file.}
|
|
|
|
\item{fmap}{feature map file representing the type of feature.
|
|
Detailed description could be found at
|
|
\url{https://github.com/tqchen/xgboost/wiki/Binary-Classification#dump-model}.
|
|
See demo/ for walkthrough example in R, and
|
|
\url{https://github.com/tqchen/xgboost/blob/master/demo/data/featmap.txt}
|
|
for example Format.}
|
|
|
|
\item{with.stats}{whether dump statistics of splits
|
|
When this option is on, the model dump comes with two additional statistics:
|
|
gain is the approximate loss function gain we get in each split;
|
|
cover is the sum of second order gradient in each node.}
|
|
}
|
|
\description{
|
|
Save a xgboost model to text file. Could be parsed later.
|
|
}
|
|
\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, nround = 2,objective = "binary:logistic")
|
|
xgb.dump(bst, 'xgb.model.dump')
|
|
}
|
|
|