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\name{ddalphaf.test}
\alias{ddalphaf.test}
\title{
Test Functional DD-Classifier
}
\description{
Trains functional DD-classifier on the learning sequence of the data and tests it on the testing sequence.
}
\usage{
ddalphaf.test(learn, learnlabels, test, testlabels, disc.type = c("LS", "comp"), ...)
}
\arguments{
\item{learn}{
list containing lists (functions) of two vectors of equal length, named "args" and "vals": arguments sorted in ascending order and corresponding them values respectively
}
\item{learnlabels}{
list of output labels of the functional observations
}
\item{test}{
the testing sequence. Has the same format as \code{learn}
}
\item{disc.type}{
type of the used discretization scheme. "LS" for \code{\link{ddalphaf.train}}, "comp" for for \code{\link{compclassf.train}}
}
\item{testlabels}{
list of output labels of the functinal observations
}
\item{\dots}{
additional parameters passed to \code{\link{ddalphaf.train}}
}
}
\value{
\item{error}{
the part of incorrectly classified data
}
\item{correct}{
the number of correctly classified objects
}
\item{incorrect}{
the number of incorrectly classified objects
}
\item{total}{
the number of classified objects
}
\item{ignored}{
the number of ignored objects (outside the convex hull of the learning data)
}
\item{n}{
the number of objects in the testing sequence
}
\item{time}{
training time
}
}
\seealso{
\code{\link{ddalphaf.train}} to train the functional DD\eqn{\alpha}-classifier,
\code{\link{ddalphaf.classify}} for classification using functonal DD\eqn{\alpha}-classifier,
\code{\link{ddalphaf.getErrorRateCV}} and \code{\link{ddalphaf.getErrorRatePart}} to get error rate of the functional DD-classifier on particular data.
}
\examples{
# load the fdata
df = dataf.growth()
samp = c(35:70)
ddalphaf.test(learn = df$dataf[-samp], learnlabels = df$labels[-samp],
test = df$dataf[samp], testlabels = df$labels[samp],
adc.args = list(instance = "avr",
numFcn = 2,
numDer = 2))
}
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{ benchmark }
|
