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add early stopping to R

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This commit is contained in:
hetong007 2015-05-05 16:31:49 -07:00
parent 3b4697786e
commit 54fb49ee5c
24 changed files with 106 additions and 31 deletions
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2
R-package/NAMESPACE
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@ -1,4 +1,4 @@
# Generated by roxygen2 (4.1.1): do not edit by hand
# Generated by roxygen2 (4.1.0): do not edit by hand
export(getinfo)
export(setinfo)

58
R-package/R/xgb.train.R
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@ -66,7 +66,11 @@
#' prediction and dtrain,
#' @param verbose If 0, xgboost will stay silent. If 1, xgboost will print
#' information of performance. If 2, xgboost will print information of both
#'
#' @param earlyStopRound 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 maximize If \code{feval} and \code{earlyStopRound} 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}.
#'
#' @details
@ -114,7 +118,8 @@
#' @export
#'
xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
obj = NULL, feval = NULL, verbose = 1, ...) {
obj = NULL, feval = NULL, verbose = 1,
earlyStopRound = NULL, maximize = NULL, ...) {
dtrain <- data
if (typeof(params) != "list") {
stop("xgb.train: first argument params must be list")
@ -133,6 +138,33 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
}
params = append(params, list(...))
# Early stopping
if (!is.null(feval) && is.null(maximize))
stop('Please set maximize to note whether the model is maximizing the evaluation or not.')
if (length(watchlist) == 0 && !is.null(earlyStopRound))
stop('For early stopping you need at least one set in watchlist.')
if (is.null(maximize) && is.null(params$eval_metric))
stop('Please set maximize to note whether the model is maximizing the evaluation or not.')
if (is.null(maximize))
{
if (params$eval_metric %in% c('rmse','logloss','error','merror','mlogloss')) {
maximize = FALSE
} else {
maximize = TRUE
}
}
if (maximize) {
bestScore = 0
} else {
bestScore = Inf
}
bestInd = 0
earlyStopflag = FALSE
if (length(watchlist)>1 && !is.null(earlyStopRound))
warning('Only the first data set in watchlist is used for early stopping process.')
handle <- xgb.Booster(params, append(watchlist, dtrain))
bst <- xgb.handleToBooster(handle)
for (i in 1:nrounds) {
@ -140,8 +172,30 @@ xgb.train <- function(params=list(), data, nrounds, watchlist = list(),
if (length(watchlist) != 0) {
msg <- xgb.iter.eval(bst$handle, watchlist, i - 1, feval)
cat(paste(msg, "\n", sep=""))
if (!is.null(earlyStopRound))
{
score = strsplit(msg,'\\s+')[[1]][1]
score = strsplit(score,':')[[1]][2]
score = as.numeric(score)
if ((maximize && score>bestScore) || (!maximize && score<bestScore)) {
bestScore = score
bestInd = i
} else {
if (i-bestInd>earlyStopRound) {
earlyStopflag = TRUE
}
}
}
}
if (earlyStopflag) {
cat('Stopping. Best iteration:',bestInd)
break
}
}
bst <- xgb.Booster.check(bst)
if (!is.null(earlyStopRound)) {
bst$bestScore = bestScore
bst$bestInd = bestInd
}
return(bst)
}

10
R-package/R/xgboost.R
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@ -30,6 +30,11 @@
#' performance and construction progress information
#' @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 earlyStopRound 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 maximize If \code{feval} and \code{earlyStopRound} 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}.
#'
#' @details
@ -51,7 +56,7 @@
#' @export
#'
xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(), nrounds,
verbose = 1, ...) {
verbose = 1, earlyStopRound = NULL, maximize = NULL, ...) {
if (is.null(missing)) {
dtrain <- xgb.get.DMatrix(data, label)
} else {
@ -66,7 +71,8 @@ xgboost <- function(data = NULL, label = NULL, missing = NULL, params = list(),
watchlist <- list()
}
bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose=verbose)
bst <- xgb.train(params, dtrain, nrounds, watchlist, verbose = verbose,
earlyStopRound = earlyStopRound)
return(bst)
}

2
R-package/man/agaricus.test.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgboost.R
\docType{data}
\name{agaricus.test}

2
R-package/man/agaricus.train.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgboost.R
\docType{data}
\name{agaricus.train}

2
R-package/man/getinfo.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/getinfo.xgb.DMatrix.R
\docType{methods}
\name{getinfo}

2
R-package/man/nrow-xgb.DMatrix-method.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/nrow.xgb.DMatrix.R
\docType{methods}
\name{nrow,xgb.DMatrix-method}

2
R-package/man/predict-xgb.Booster-method.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/predict.xgb.Booster.R
\docType{methods}
\name{predict,xgb.Booster-method}

2
R-package/man/predict-xgb.Booster.handle-method.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/predict.xgb.Booster.handle.R
\docType{methods}
\name{predict,xgb.Booster.handle-method}

2
R-package/man/setinfo.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/setinfo.xgb.DMatrix.R
\docType{methods}
\name{setinfo}

2
R-package/man/slice.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/slice.xgb.DMatrix.R
\docType{methods}
\name{slice}

2
R-package/man/xgb.DMatrix.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.DMatrix.R
\name{xgb.DMatrix}
\alias{xgb.DMatrix}

2
R-package/man/xgb.DMatrix.save.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.DMatrix.save.R
\name{xgb.DMatrix.save}
\alias{xgb.DMatrix.save}

2
R-package/man/xgb.cv.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.cv.R
\name{xgb.cv}
\alias{xgb.cv}

2
R-package/man/xgb.dump.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.dump.R
\name{xgb.dump}
\alias{xgb.dump}

2
R-package/man/xgb.importance.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.importance.R
\name{xgb.importance}
\alias{xgb.importance}

2
R-package/man/xgb.load.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.load.R
\name{xgb.load}
\alias{xgb.load}

2
R-package/man/xgb.model.dt.tree.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.model.dt.tree.R
\name{xgb.model.dt.tree}
\alias{xgb.model.dt.tree}

2
R-package/man/xgb.plot.importance.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.plot.importance.R
\name{xgb.plot.importance}
\alias{xgb.plot.importance}

2
R-package/man/xgb.plot.tree.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.plot.tree.R
\name{xgb.plot.tree}
\alias{xgb.plot.tree}

2
R-package/man/xgb.save.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.save.R
\name{xgb.save}
\alias{xgb.save}

2
R-package/man/xgb.save.raw.Rd
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@ -1,4 +1,4 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.save.raw.R
\name{xgb.save.raw}
\alias{xgb.save.raw}

16
R-package/man/xgb.train.Rd
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@ -1,11 +1,12 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgb.train.R
\name{xgb.train}
\alias{xgb.train}
\title{eXtreme Gradient Boosting Training}
\usage{
xgb.train(params = list(), data, nrounds, watchlist = list(), obj = NULL,
feval = NULL, verbose = 1, ...)
feval = NULL, verbose = 1, earlyStopRound = NULL, maximize = NULL,
...)
}
\arguments{
\item{params}{the list of parameters.
@ -49,7 +50,7 @@ xgb.train(params = list(), data, nrounds, watchlist = list(), obj = NULL,
\item \code{binary:logistic} logistic regression for binary classification. Output probability.
\item \code{binary:logitraw} logistic regression for binary classification, output score before logistic transformation.
\item \code{num_class} set the number of classes. To use only with multiclass objectives.
\item \code{multi:softmax} set xgboost to do multiclass classification using the softmax objective. Class is a number and should be from 0 \code{tonum_class}
\item \code{multi:softmax} set xgboost to do multiclass classification using the softmax objective. Class is represented by a number and should be from 0 to \code{tonum_class}.
\item \code{multi:softprob} same as softmax, but output a vector of ndata * nclass, which can be further reshaped to ndata, nclass matrix. The result contains predicted probabilities of each data point belonging to each class.
\item \code{rank:pairwise} set xgboost to do ranking task by minimizing the pairwise loss.
}
@ -77,6 +78,13 @@ prediction and dtrain,}
\item{verbose}{If 0, xgboost will stay silent. If 1, xgboost will print
information of performance. If 2, xgboost will print information of both}
\item{earlyStopRound}{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.}
\item{maximize}{If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
\code{maximize=TRUE} means the larger the evaluation score the better.}
\item{...}{other parameters to pass to \code{params}.}
}
\description{
@ -98,7 +106,7 @@ Number of threads can also be manually specified via \code{nthread} parameter.
\item \code{error} Binary classification error rate. It is calculated as \code{(wrong cases) / (all cases)}. For the predictions, the evaluation will regard the instances with prediction value larger than 0.5 as positive instances, and the others as negative instances.
\item \code{merror} Multiclass classification error rate. It is calculated as \code{(wrong cases) / (all cases)}.
\item \code{auc} Area under the curve. \url{http://en.wikipedia.org/wiki/Receiver_operating_characteristic#'Area_under_curve} for ranking evaluation.
\item \code{ndcg} Normalized Discounted Cumulative Gain. \url{http://en.wikipedia.org/wiki/NDCG}
\item \code{ndcg} Normalized Discounted Cumulative Gain (for ranking task). \url{http://en.wikipedia.org/wiki/NDCG}
}
Full list of parameters is available in the Wiki \url{https://github.com/dmlc/xgboost/wiki/Parameters}.

11
R-package/man/xgboost.Rd
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@ -1,11 +1,11 @@
% Generated by roxygen2 (4.1.1): do not edit by hand
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/xgboost.R
\name{xgboost}
\alias{xgboost}
\title{eXtreme Gradient Boosting (Tree) library}
\usage{
xgboost(data = NULL, label = NULL, missing = NULL, params = list(),
nrounds, verbose = 1, ...)
nrounds, verbose = 1, earlyStopRound = NULL, maximize = NULL, ...)
}
\arguments{
\item{data}{takes \code{matrix}, \code{dgCMatrix}, local data file or
@ -41,6 +41,13 @@ Commonly used ones are:
information of performance. If 2, xgboost will print information of both
performance and construction progress information}
\item{earlyStopRound}{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.}
\item{maximize}{If \code{feval} and \code{earlyStopRound} are set, then \code{maximize} must be set as well.
\code{maximize=TRUE} means the larger the evaluation score the better.}
\item{...}{other parameters to pass to \code{params}.}
}
\description{