saveRDS.lgb.Booster.Rd 2.05 KB
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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/saveRDS.lgb.Booster.R
\name{saveRDS.lgb.Booster}
\alias{saveRDS.lgb.Booster}
\title{saveRDS for lgb.Booster models}
\usage{
saveRDS.lgb.Booster(object, file = "", ascii = FALSE, version = NULL,
  compress = TRUE, refhook = NULL, raw = TRUE)
}
\arguments{
\item{object}{R object to serialize.}

\item{file}{a connection or the name of the file where the R object is saved to or read from.}

\item{ascii}{a logical. If TRUE or NA, an ASCII representation is written; otherwise (default), a binary one is used. See the comments in the help for save.}

\item{version}{the workspace format version to use. \code{NULL} specifies the current default version (2). Versions prior to 2 are not supported, so this will only be relevant when there are later versions.}

\item{compress}{a logical specifying whether saving to a named file is to use "gzip" compression, or one of \code{"gzip"}, \code{"bzip2"} or \code{"xz"} to indicate the type of compression to be used. Ignored if file is a connection.}

\item{refhook}{a hook function for handling reference objects.}

\item{raw}{whether to save the model in a raw variable or not, recommended to leave it to \code{TRUE}.}
}
\value{
NULL invisibly.
}
\description{
Attemps to save a model using RDS. Has an additional parameter (\code{raw}) which decides whether to save the raw model or not.
}
\examples{
\dontrun{
  library(lightgbm)
  data(agaricus.train, package = "lightgbm")
  train <- agaricus.train
  dtrain <- lgb.Dataset(train$data, label = train$label)
  data(agaricus.test, package = "lightgbm")
  test <- agaricus.test
  dtest <- lgb.Dataset.create.valid(dtrain, test$data, label = test$label)
  params <- list(objective = "regression", metric = "l2")
  valids <- list(test = dtest)
  model <- lgb.train(params,
                     dtrain,
                     100,
                     valids,
                     min_data = 1,
                     learning_rate = 1,
                     early_stopping_rounds = 10)
  saveRDS.lgb.Booster(model, "model.rds")
}

}