support both early stop name
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@ -66,10 +66,11 @@
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#' prediction and dtrain,
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#' prediction and dtrain,
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#' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print
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#' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print
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#' information of performance. If 2, xgboost will print information of both
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#' information of performance. If 2, xgboost will print information of both
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#' @param earlyStopRound If \code{NULL}, the early stopping function is not triggered.
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#' @param early_stop_round If \code{NULL}, the early stopping function is not triggered.
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#' If set to an integer \code{k}, training with a validation set will stop if the performance
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#' If set to an integer \code{k}, training with a validation set will stop if the performance
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#' keeps getting worse consecutively for \code{k} rounds.
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#' keeps getting worse consecutively for \code{k} rounds.
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#' @param maximize If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
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#' @param early.stop.round An alternative of \code{early_stop_round}.
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#' @param maximize If \code{feval} and \code{early_stop_round} are set, then \code{maximize} must be set as well.
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#' \code{maximize=TRUE} means the larger the evaluation score the better.
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#' \code{maximize=TRUE} means the larger the evaluation score the better.
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#' @param ... other parameters to pass to \code{params}.
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#' @param ... other parameters to pass to \code{params}.
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#'
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#'
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@ -119,7 +120,8 @@
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#'
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#'
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xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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obj = NULL, feval = NULL, verbose = 1,
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obj = NULL, feval = NULL, verbose = 1,
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earlyStopRound = NULL, maximize = NULL, ...) {
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early_stop_round = NULL, early.stop.round = NULL,
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maximize = NULL, ...) {
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dtrain <- data
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dtrain <- data
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if (typeof(params) != "list") {
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if (typeof(params) != "list") {
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stop("xgb.train: first argument params must be list")
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stop("xgb.train: first argument params must be list")
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@ -139,7 +141,9 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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params = append(params, list(...))
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params = append(params, list(...))
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# Early stopping
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# Early stopping
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if (!is.null(earlyStopRound)){
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if (is.null(early_stop_round) && !is.null(early.stop.round))
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early_stop_round = early.stop.round
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if (!is.null(early_stop_round)){
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if (!is.null(feval) && is.null(maximize))
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if (!is.null(feval) && is.null(maximize))
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stop('Please set maximize to note whether the model is maximizing the evaluation or not.')
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stop('Please set maximize to note whether the model is maximizing the evaluation or not.')
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if (length(watchlist) == 0)
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if (length(watchlist) == 0)
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@ -175,7 +179,7 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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if (length(watchlist) != 0) {
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if (length(watchlist) != 0) {
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msg <- xgb.iter.eval(bst$handle, watchlist, i - 1, feval)
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msg <- xgb.iter.eval(bst$handle, watchlist, i - 1, feval)
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cat(paste(msg, "\n", sep=""))
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cat(paste(msg, "\n", sep=""))
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if (!is.null(earlyStopRound))
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if (!is.null(early_stop_round))
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{
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{
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score = strsplit(msg,':|\\s+')[[1]][3]
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score = strsplit(msg,':|\\s+')[[1]][3]
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score = as.numeric(score)
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score = as.numeric(score)
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@ -183,7 +187,7 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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bestScore = score
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bestScore = score
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bestInd = i
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bestInd = i
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} else {
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} else {
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if (i-bestInd>earlyStopRound) {
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if (i-bestInd>early_stop_round) {
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earlyStopflag = TRUE
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earlyStopflag = TRUE
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cat('Stopping. Best iteration:',bestInd)
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cat('Stopping. Best iteration:',bestInd)
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break
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break
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@ -193,7 +197,7 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
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}
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}
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}
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}
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bst <- xgb.Booster.check(bst)
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bst <- xgb.Booster.check(bst)
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if (!is.null(earlyStopRound)) {
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if (!is.null(early_stop_round)) {
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bst$bestScore = bestScore
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bst$bestScore = bestScore
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bst$bestInd = bestInd
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bst$bestInd = bestInd
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}
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}
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@ -30,10 +30,11 @@
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#' performance and construction progress information
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#' performance and construction progress information
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#' @param missing Missing is only used when input is dense matrix, pick a float
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#' @param missing Missing is only used when input is dense matrix, pick a float
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#' value that represents missing value. Sometimes a data use 0 or other extreme value to represents missing values.
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#' value that represents missing value. Sometimes a data use 0 or other extreme value to represents missing values.
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#' @param earlyStopRound If \code{NULL}, the early stopping function is not triggered.
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#' @param early_stop_round If \code{NULL}, the early stopping function is not triggered.
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#' If set to an integer \code{k}, training with a validation set will stop if the performance
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#' If set to an integer \code{k}, training with a validation set will stop if the performance
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#' keeps getting worse consecutively for \code{k} rounds.
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#' keeps getting worse consecutively for \code{k} rounds.
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#' @param maximize If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
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#' @param early.stop.round An alternative of \code{early_stop_round}.
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#' @param maximize If \code{feval} and \code{early_stop_round} are set, then \code{maximize} must be set as well.
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#' \code{maximize=TRUE} means the larger the evaluation score the better.
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#' \code{maximize=TRUE} means the larger the evaluation score the better.
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#' @param ... other parameters to pass to \code{params}.
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#' @param ... other parameters to pass to \code{params}.
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#'
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#'
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@ -56,7 +57,8 @@
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#' @export
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#' @export
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#'
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#'
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xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(), nrounds,
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xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(), nrounds,
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verbose = 1, earlyStopRound = NULL, maximize = NULL, ...) {
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verbose = 1, early_stop_round = NULL, early.stop.round = NULL,
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maximize = NULL, ...) {
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if (is.null(missing)) {
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if (is.null(missing)) {
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dtrain <- xgb.get.DMatrix(data, label)
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dtrain <- xgb.get.DMatrix(data, label)
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} else {
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} else {
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@ -72,7 +74,8 @@ xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(),
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}
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}
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bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose = verbose,
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bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose = verbose,
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earlyStopRound = earlyStopRound)
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early_stop_round = early_stop_round,
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early.stop.round = early.stop.round)
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return(bst)
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return(bst)
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}
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}
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@ -5,8 +5,8 @@
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\title{eXtreme Gradient Boosting Training}
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\title{eXtreme Gradient Boosting Training}
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\usage{
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\usage{
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xgb.train(params = list(), data, nrounds, watchlist = list(), obj = NULL,
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xgb.train(params = list(), data, nrounds, watchlist = list(), obj = NULL,
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feval = NULL, verbose = 1, earlyStopRound = NULL, maximize = NULL,
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feval = NULL, verbose = 1, early_stop_round = NULL,
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...)
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early.stop.round = NULL, maximize = NULL, ...)
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}
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}
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\arguments{
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\arguments{
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\item{params}{the list of parameters.
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\item{params}{the list of parameters.
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@ -78,11 +78,13 @@ prediction and dtrain,}
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\item{verbose}{If 0, xgboost will stay silent. If 1, xgboost will print
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\item{verbose}{If 0, xgboost will stay silent. If 1, xgboost will print
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information of performance. If 2, xgboost will print information of both}
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information of performance. If 2, xgboost will print information of both}
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\item{earlyStopRound}{If \code{NULL}, the early stopping function is not triggered.
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\item{early_stop_round}{If \code{NULL}, the early stopping function is not triggered.
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If set to an integer \code{k}, training with a validation set will stop if the performance
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If set to an integer \code{k}, training with a validation set will stop if the performance
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keeps getting worse consecutively for \code{k} rounds.}
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keeps getting worse consecutively for \code{k} rounds.}
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\item{maximize}{If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
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\item{early.stop.round}{An alternative of \code{early_stop_round}.}
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\item{maximize}{If \code{feval} and \code{early_stop_round} are set, then \code{maximize} must be set as well.
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\code{maximize=TRUE} means the larger the evaluation score the better.}
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\code{maximize=TRUE} means the larger the evaluation score the better.}
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\item{...}{other parameters to pass to \code{params}.}
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\item{...}{other parameters to pass to \code{params}.}
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@ -5,7 +5,8 @@
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\title{eXtreme Gradient Boosting (Tree) library}
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\title{eXtreme Gradient Boosting (Tree) library}
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\usage{
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\usage{
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xgboost(data = NULL, label = NULL, missing = NULL, params = list(),
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xgboost(data = NULL, label = NULL, missing = NULL, params = list(),
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nrounds, verbose = 1, earlyStopRound = NULL, maximize = NULL, ...)
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nrounds, verbose = 1, early_stop_round = NULL, early.stop.round = NULL,
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maximize = NULL, ...)
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}
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}
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\arguments{
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\arguments{
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\item{data}{takes \code{matrix}, \code{dgCMatrix}, local data file or
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\item{data}{takes \code{matrix}, \code{dgCMatrix}, local data file or
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@ -41,11 +42,13 @@ Commonly used ones are:
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information of performance. If 2, xgboost will print information of both
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information of performance. If 2, xgboost will print information of both
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performance and construction progress information}
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performance and construction progress information}
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\item{earlyStopRound}{If \code{NULL}, the early stopping function is not triggered.
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\item{early_stop_round}{If \code{NULL}, the early stopping function is not triggered.
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If set to an integer \code{k}, training with a validation set will stop if the performance
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If set to an integer \code{k}, training with a validation set will stop if the performance
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keeps getting worse consecutively for \code{k} rounds.}
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keeps getting worse consecutively for \code{k} rounds.}
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\item{maximize}{If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
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\item{early.stop.round}{An alternative of \code{early_stop_round}.}
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\item{maximize}{If \code{feval} and \code{early_stop_round} are set, then \code{maximize} must be set as well.
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\code{maximize=TRUE} means the larger the evaluation score the better.}
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\code{maximize=TRUE} means the larger the evaluation score the better.}
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\item{...}{other parameters to pass to \code{params}.}
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\item{...}{other parameters to pass to \code{params}.}
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