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%
% Copyright (c) 2012, 2014, Oracle and/or its affiliates. All rights reserved. 
%
\name{ore.predict-multinom}
\alias{ore.predict-multinom}
\alias{ore.predict,multinom-method}
\title{Oracle R Enterprise Predictions Using \code{\link[nnet]{multinom}} Models}
\description{
  Oracle R Enterprise method for generating predictions using
  \code{\link[nnet]{multinom}} models.
}
\usage{
  \S4method{ore.predict}{multinom}(object, newdata, type = c("class", "probs"),
            na.action = na.pass, ...)
}
\arguments{
  \item{object}{An \code{\link[nnet]{multinom}} model object.}
  \item{newdata}{An \code{\link[OREbase:ore.frame-class]{ore.frame}}
    object.}
  \item{type}{A character string specifying the type of prediction to
    make; either \code{"class"} or \code{"probs"}.}
  \item{na.action}{The manner in which \code{NA} values are handled,
    either \code{na.omit} or \code{na.pass}.}
  \item{\dots}{Optional arguments.}
}
\value{
  Returns an object of an \code{\link[OREbase:ore-class]{ore}} subclass.
}
\references{
  \href{http://www.oracle.com/technetwork/database/database-technologies/r/r-enterprise/documentation/index.html}{Oracle R Enterprise}
}
\author{
  Oracle \email{oracle-r-enterprise@oracle.com}
}
\seealso{
  \code{\link{ore.predict}},
  \code{\link[nnet]{predict.multinom}}.
}
\examples{
library(nnet)
model <- multinom(Species ~ ., data = iris)
IRIS <- ore.push(iris)
IRIS <- cbind(IRIS, ore.predict(model, IRIS, type = "probs"))
head(IRIS)
}
\keyword{models}

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