saveRDS.lgb.Booster.Rd 2.24 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}
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\title{saveRDS for \code{lgb.Booster} models (DEPRECATED)}
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\usage{
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saveRDS.lgb.Booster(
  object,
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  file,
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  ascii = FALSE,
  version = NULL,
  compress = TRUE,
  refhook = NULL,
  raw = TRUE
)
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}
\arguments{
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\item{object}{\code{lgb.Booster} object to serialize.}
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\item{file}{a connection or the name of the file where the R object is saved to or read from.}

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\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.}
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\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.}
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\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.}
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\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{
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Calls \code{saveRDS} on an \code{lgb.Booster} object, making it serializable before the call if
             it isn't already.

             \bold{This function throws a warning and will be removed in future versions.}
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}
\examples{
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\donttest{
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library(lightgbm)
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\dontshow{setLGBMthreads(2L)}
\dontshow{data.table::setDTthreads(1L)}
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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)
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params <- list(
  objective = "regression"
  , metric = "l2"
  , min_data = 1L
  , learning_rate = 1.0
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  , num_threads = 2L
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)
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valids <- list(test = dtest)
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model <- lgb.train(
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    params = params
    , data = dtrain
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    , nrounds = 10L
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    , valids = valids
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    , early_stopping_rounds = 5L
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)
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model_file <- tempfile(fileext = ".rds")
saveRDS.lgb.Booster(model, model_file)
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}
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}