MINI MINI MANI MO

%
% Copyright (c) 2012, 2014, Oracle and/or its affiliates. All rights reserved. 
%
\name{ore.predict-kmeans}
\alias{ore.predict-kmeans}
\alias{ore.predict,kmeans-method}
\title{Oracle R Enterprise Predictions Using \code{\link[stats]{kmeans}} Models}
\description{
  Oracle R Enterprise method for generating predictions using
  \code{\link[stats]{kmeans}} Models.
}
\usage{
  \S4method{ore.predict}{kmeans}(object, newdata, type = c("classes", "distances"),
            na.action = na.pass, ...)
}
\arguments{
  \item{object}{A \code{\link[stats]{kmeans}} 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{"classes"} (cluster id) or \code{"distances"}
    (Euclidean distance from cluster centers).}
  \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{
  If argument \code{type} is \code{"classes"}, returns an
  \code{\link[OREbase:ore.integer-class]{ore.integer}} object of
  cluster classifications.

  If argument \code{type} is \code{"distances"}, returns an
  \code{\link[OREbase:ore.frame-class]{ore.frame}} object with one
  column for each cluster.
}
\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{ore.predict-matrix}},
  \code{\link[stats]{kmeans}}.
}
\examples{
irisClusters <- kmeans(as.matrix(iris[1:4]), centers = 3)
IRIS <- ore.push(iris)
IRIS$CLUSTER <- ore.predict(irisClusters, IRIS)
IRIS <- cbind(IRIS, ore.predict(irisClusters, IRIS, type = "distances"))
head(IRIS)
table(IRIS$CLUSTER, IRIS$Species)
}
\keyword{multivariate}
\keyword{cluster}