a375ad2822
* [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
43 lines
1.7 KiB
R
43 lines
1.7 KiB
R
#' Save xgboost model to binary file
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#'
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#' Save xgboost model to a file in binary 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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#' @details
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#' This methods allows to save a model in an xgboost-internal binary 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.
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#'
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#' @seealso
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#' \code{\link{xgb.load}}, \code{\link{xgb.Booster.complete}}.
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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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#' train <- agaricus.train
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#' test <- agaricus.test
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#' bst <- xgboost(data = train$data, label = train$label, max_depth = 2,
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#' eta = 1, nthread = 2, nrounds = 2,objective = "binary:logistic")
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#' xgb.save(bst, 'xgb.model')
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#' bst <- xgb.load('xgb.model')
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#' pred <- predict(bst, test$data)
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#' @export
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xgb.save <- function(model, fname) {
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if (typeof(fname) != "character")
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stop("fname must be character")
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if (!inherits(model, "xgb.Booster")) {
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stop("model must be xgb.Booster.",
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if (inherits(model, "xgb.DMatrix")) " Use xgb.DMatrix.save to save an xgb.DMatrix object." else "")
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}
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model <- xgb.Booster.complete(model, saveraw = FALSE)
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.Call("XGBoosterSaveModel_R", model$handle, fname[1], PACKAGE = "xgboost")
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return(TRUE)
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}
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