Hendrik/xgboost
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rename arguments to be dot-seperated

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hetong007
2015-05-25 11:51:01 -07:00
parent 8d3a7e1688
commit 733d23aef8
6 changed files with 40 additions and 55 deletions
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12
R-package/R/xgboost.R
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@@ -28,14 +28,13 @@
#' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print
#' information of performance. If 2, xgboost will print information of both
#' performance and construction progress information
#' @param printEveryN Print every N progress messages when \code{verbose>0}. Default is 1 which means all messages are printed.
#' @param print.every.n Print every N progress messages when \code{verbose>0}. Default is 1 which means all messages are printed.
#' @param missing Missing is only used when input is dense matrix, pick a float
#' value that represents missing value. Sometimes a data use 0 or other extreme value to represents missing values.
#' @param early_stop_round If \code{NULL}, the early stopping function is not triggered.
#' @param early.stop.round If \code{NULL}, the early stopping function is not triggered.
#' If set to an integer \code{k}, training with a validation set will stop if the performance
#' keeps getting worse consecutively for \code{k} rounds.
#' @param early.stop.round An alternative of \code{early_stop_round}.
#' @param maximize If \code{feval} and \code{early_stop_round} are set, then \code{maximize} must be set as well.
#' @param maximize If \code{feval} and \code{early.stop.round} are set, then \code{maximize} must be set as well.
#' \code{maximize=TRUE} means the larger the evaluation score the better.
#' @param ... other parameters to pass to \code{params}.
#'
@@ -58,7 +57,7 @@
#' @export
#'
xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(), nrounds,
verbose = 1, printEveryN=1L, early_stop_round = NULL, early.stop.round = NULL,
verbose = 1, print.every.n = 1L, early.stop.round = NULL,
maximize = NULL, ...) {
if (is.null(missing)) {
dtrain <- xgb.get.DMatrix(data, label)
@@ -74,8 +73,7 @@ xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(),
watchlist <- list()
}
bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose = verbose, printEveryN=printEveryN,
early_stop_round = early_stop_round,
bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose = verbose, print.every.n=print.every.n,
early.stop.round = early.stop.round)
return(bst)