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Merge branch 'master' of ssh://github.com/tqchen/xgboost

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Conflicts:
	src/utils/omp.h
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tqchen 2014-09-01 17:03:20 -07:00
commit 2f6a64e8fa
3 changed files with 11 additions and 7 deletions
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4
R-package/R/predict.xgb.Booster.R
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@ -12,7 +12,7 @@ setClass("xgb.Booster")
#' untransformed margin value. In logistic regression, outputmargin=T will #' untransformed margin value. In logistic regression, outputmargin=T will
#' output value before logistic transformation. #' output value before logistic transformation.
#' @param ntreelimit limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear. #' @param ntreelimit limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear.
#' set it to be value bigger than 0 #' set it to be value bigger than 0. It will use all trees by default.
#' @examples #' @examples
#' data(iris) #' data(iris)
#' bst <- xgboost(as.matrix(iris[,1:4]),as.numeric(iris[,5]), nrounds = 2) #' bst <- xgboost(as.matrix(iris[,1:4]),as.numeric(iris[,5]), nrounds = 2)
@ -28,7 +28,7 @@ setMethod("predict", signature = "xgb.Booster",
ntreelimit <- 0 ntreelimit <- 0
} else { } else {
if (ntreelimit < 1){ if (ntreelimit < 1){
stop("predict: ntreelimit must be greater equal than 1") stop("predict: ntreelimit must be equal to or greater than 1")
} }
} }
ret <- .Call("XGBoosterPredict_R", object, newdata, as.integer(outputmargin), as.integer(ntreelimit), PACKAGE = "xgboost") ret <- .Call("XGBoosterPredict_R", object, newdata, as.integer(outputmargin), as.integer(ntreelimit), PACKAGE = "xgboost")

12
R-package/man/predict-xgb.Booster-method.Rd
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@ -4,7 +4,8 @@
\alias{predict,xgb.Booster-method} \alias{predict,xgb.Booster-method}
\title{Predict method for eXtreme Gradient Boosting model} \title{Predict method for eXtreme Gradient Boosting model}
\usage{ \usage{
\S4method{predict}{xgb.Booster}(object, newdata, outputmargin = FALSE) \S4method{predict}{xgb.Booster}(object, newdata, outputmargin = FALSE,
ntreelimit = NULL)
} }
\arguments{ \arguments{
\item{object}{Object of class "xgb.Boost"} \item{object}{Object of class "xgb.Boost"}
@ -13,9 +14,12 @@
\code{xgb.DMatrix}.} \code{xgb.DMatrix}.}
\item{outputmargin}{whether the prediction should be shown in the original \item{outputmargin}{whether the prediction should be shown in the original
value of sum of functions, when outputmargin=TRUE, the prediction is value of sum of functions, when outputmargin=TRUE, the prediction is
untransformed margin value. In logistic regression, outputmargin=T will untransformed margin value. In logistic regression, outputmargin=T will
output value before logistic transformation.} output value before logistic transformation.}
\item{ntreelimit}{limit number of trees used in prediction, this parameter is only valid for gbtree, but not for gblinear.
set it to be value bigger than 0. It will use all trees by default.}
} }
\description{ \description{
Predicted values based on xgboost model object. Predicted values based on xgboost model object.

2
src/utils/omp.h
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@ -10,7 +10,7 @@
#else #else
#ifndef DISABLE_OPENMP #ifndef DISABLE_OPENMP
// use pragma message instead of warning // use pragma message instead of warning
#pragma message ("Warning: OpenMP is not available. XGBoost will be compiled with single thread mode. You may want to use compiler with OpenMP support to get benefit of multi-threading.") #pragma message ("Warning: OpenMP is not available, xgboost will be compiled into single-thread code. Use OpenMP-enabled compiler to get benefit of multi-threading")
#endif #endif
inline int omp_get_thread_num() { return 0; } inline int omp_get_thread_num() { return 0; }
inline int omp_get_num_threads() { return 1; } inline int omp_get_num_threads() { return 1; }