70 lines
2.9 KiB
R
70 lines
2.9 KiB
R
#' Save xgboost model to binary file
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#'
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#' Save xgboost model to a file in binary or JSON format.
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#'
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#' @param model Model object of \code{xgb.Booster} class.
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#' @param fname Name of the file to write.
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#'
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#' Note that the extension of this file name determined the serialization format to use:\itemize{
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#' \item Extension ".ubj" will use the universal binary JSON format (recommended).
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#' This format uses binary types for e.g. floating point numbers, thereby preventing any loss
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#' of precision when converting to a human-readable JSON text or similar.
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#' \item Extension ".json" will use plain JSON, which is a human-readable format.
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#' \item Extension ".deprecated" will use a \bold{deprecated} binary format. This format will
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#' not be able to save attributes introduced after v1 of XGBoost, such as the "best_iteration"
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#' attribute that boosters might keep, nor feature names or user-specifiec attributes.
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#' \item If the format is not specified by passing one of the file extensions above, will
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#' default to UBJ.
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#' }
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#'
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#' @details
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#' This methods allows to save a model in an xgboost-internal binary or text format which is universal
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#' among the various xgboost interfaces. In R, the saved model file could be read-in later
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#' using either the \code{\link{xgb.load}} function or the \code{xgb_model} parameter
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#' of \code{\link{xgb.train}}.
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#'
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#' Note: a model can also be saved as an R-object (e.g., by using \code{\link[base]{readRDS}}
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#' or \code{\link[base]{save}}). However, it would then only be compatible with R, and
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#' corresponding R-methods would need to be used to load it. Moreover, persisting the model with
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#' \code{\link[base]{readRDS}} or \code{\link[base]{save}}) might cause compatibility problems in
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#' future versions of XGBoost. Consult \code{\link{a-compatibility-note-for-saveRDS-save}} to learn
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#' how to persist models in a future-proof way, i.e. to make the model accessible in future
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#' releases of XGBoost.
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#'
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#' @seealso
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#' \code{\link{xgb.load}}
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#'
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#' @examples
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#' data(agaricus.train, package='xgboost')
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#' data(agaricus.test, package='xgboost')
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#'
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#' ## Keep the number of threads to 1 for examples
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#' nthread <- 1
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#' data.table::setDTthreads(nthread)
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#'
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#' train <- agaricus.train
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#' test <- agaricus.test
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#' bst <- xgb.train(
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#' data = xgb.DMatrix(train$data, label = train$label),
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#' max_depth = 2,
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#' eta = 1,
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#' nthread = nthread,
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#' nrounds = 2,
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#' objective = "binary:logistic"
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#' )
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#' fname <- file.path(tempdir(), "xgb.ubj")
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#' xgb.save(bst, fname)
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#' bst <- xgb.load(fname)
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#' @export
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xgb.save <- function(model, fname) {
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if (typeof(fname) != "character")
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stop("fname must be character")
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if (!inherits(model, "xgb.Booster")) {
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stop("model must be xgb.Booster.",
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if (inherits(model, "xgb.DMatrix")) " Use xgb.DMatrix.save to save an xgb.DMatrix object." else "")
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}
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fname <- path.expand(fname)
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.Call(XGBoosterSaveModel_R, xgb.get.handle(model), enc2utf8(fname[1]))
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return(TRUE)
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}
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