2b5b96d760
* [R] xgb.save must work when handle in nil but raw exists * [R] print.xgb.Booster should still print other info when handle is nil * [R] rename internal function xgb.Booster to xgb.Booster.handle to make its intent clear * [R] rename xgb.Booster.check to xgb.Booster.complete and make it visible; more docs * [R] storing evaluation_log should depend only on watchlist, not on verbose * [R] reduce the excessive chattiness of unit tests * [R] only disable some tests in windows when it's not 64-bit * [R] clean-up xgb.DMatrix * [R] test xgb.DMatrix loading from libsvm text file * [R] store feature_names in xgb.Booster, use them from utility functions * [R] remove non-functional co-occurence computation from xgb.importance * [R] verbose=0 is enough without a callback * [R] added forgotten xgb.Booster.complete.Rd; cran check fixes * [R] update installation instructions
72 lines
2.9 KiB
R
72 lines
2.9 KiB
R
#' Dump an xgboost model in text format.
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#'
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#' Dump an xgboost model in text format.
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#'
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#' @param model the model object.
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#' @param fname the name of the text file where to save the model text dump.
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#' If not provided or set to \code{NULL}, the model is returned as a \code{character} vector.
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#' @param fmap feature map file representing feature types.
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#' Detailed description could be found at
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#' \url{https://github.com/dmlc/xgboost/wiki/Binary-Classification#dump-model}.
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#' See demo/ for walkthrough example in R, and
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#' \url{https://github.com/dmlc/xgboost/blob/master/demo/data/featmap.txt}
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#' for example Format.
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#' @param with_stats whether to dump some additional statistics about the splits.
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#' When this option is on, the model dump contains two additional values:
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#' gain is the approximate loss function gain we get in each split;
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#' cover is the sum of second order gradient in each node.
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#' @param dump_format either 'text' or 'json' format could be specified.
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#' @param ... currently not used
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#'
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#' @return
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#' If fname is not provided or set to \code{NULL} the function will return the model
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#' as a \code{character} vector. Otherwise it will return \code{TRUE}.
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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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#' # save the model in file 'xgb.model.dump'
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#' xgb.dump(bst, 'xgb.model.dump', with_stats = TRUE)
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#'
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#' # print the model without saving it to a file
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#' print(xgb.dump(bst, with_stats = TRUE))
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#'
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#' # print in JSON format:
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#' cat(xgb.dump(bst, with_stats = TRUE, dump_format='json'))
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#'
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#' @export
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xgb.dump <- function(model = NULL, fname = NULL, fmap = "", with_stats=FALSE,
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dump_format = c("text", "json"), ...) {
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check.deprecation(...)
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dump_format <- match.arg(dump_format)
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if (class(model) != "xgb.Booster")
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stop("model: argument must be of type xgb.Booster")
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if (!(class(fname) %in% c("character", "NULL") && length(fname) <= 1))
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stop("fname: argument must be of type character (when provided)")
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if (!(class(fmap) %in% c("character", "NULL") && length(fmap) <= 1))
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stop("fmap: argument must be of type character (when provided)")
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model <- xgb.Booster.complete(model)
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model_dump <- .Call("XGBoosterDumpModel_R", model$handle, fmap, as.integer(with_stats),
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as.character(dump_format), PACKAGE = "xgboost")
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if (is.null(fname))
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model_dump <- stri_replace_all_regex(model_dump, '\t', '')
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if (dump_format == "text")
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model_dump <- unlist(stri_split_regex(model_dump, '\n'))
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model_dump <- grep('^\\s*$', model_dump, invert = TRUE, value = TRUE)
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if (is.null(fname)) {
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return(model_dump)
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} else {
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writeLines(model_dump, fname)
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return(TRUE)
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}
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}
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