xgboost/R-package/man/xgboost.Rd
2014-12-28 10:46:31 +01:00

58 lines
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R

% 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, ...)
}
\arguments{
\item{data}{takes \code{matrix}, \code{dgCMatrix}, local data file or
\code{xgb.DMatrix}.}
\item{label}{the response variable. User should not set this field,}
\item{params}{the list of parameters. Commonly used ones are:
\itemize{
\item \code{objective} objective function, common ones are
\itemize{
\item \code{reg:linear} linear regression
\item \code{binary:logistic} logistic regression for classification
}
\item \code{eta} step size of each boosting step
\item \code{max.depth} maximum depth of the tree
\item \code{nthread} number of thread used in training, if not set, all threads are used
}
See \url{https://github.com/tqchen/xgboost/wiki/Parameters} for
further details. See also demo/ for walkthrough example in R.}
\item{nrounds}{the max number of iterations}
\item{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}
\item{...}{other parameters to pass to \code{params}.}
}
\description{
A simple interface for xgboost in R
}
\details{
This is the modeling function for xgboost.
Parallelization is automatically enabled if OpenMP is present.
Number of threads can also be manually specified via "nthread" parameter
}
\examples{
data(agaricus.train, package='xgboost')
data(agaricus.test, package='xgboost')
train <- agaricus.train
test <- agaricus.test
bst <- xgboost(data = train$data, label = train$label, max.depth = 2,
eta = 1, nround = 2,objective = "binary:logistic")
pred <- predict(bst, test$data)
}