\HeaderA{cloutput-class}{"cloutput"}{cloutput.Rdash.class}
\aliasA{cloutput}{cloutput-class}{cloutput}
\aliasA{show,cloutput-method}{cloutput-class}{show,cloutput.Rdash.method}
\keyword{multivariate}{cloutput-class}
\begin{Description}\relax
Object returned by one of the classifiers (functions ending with \code{CMA})
\end{Description}
\begin{Section}{Slots}
\describe{
\item[\code{learnind}:] Vector of indices that indicates which observations
where used in the learning set.
\item[\code{y}:] Actual (true) class labels of predicted observations.
\item[\code{yhat}:] Predicted class labels by the classifier.
\item[\code{prob}:] A \code{numeric} \code{matrix} whose rows
equals the number of predicted observations (length of \code{y}/\code{yhat})
and whose columns equal the number of different classes in the learning set.
Rows add up to one.
Entry \code{j,k} of this matrix contains the probability for the \code{j}-th
predicted observation to belong to class \code{k}.
Can be a matrix of \code{NA}s, if the classifier used does not
provide any probabilities
\item[\code{method}:] Name of the classifer used.
\item[\code{mode}:] \code{character}, one of \code{"binary"} (if the number of classes in the learning set is two)
or \code{multiclass} (if it is more than two).
}
\end{Section}
\begin{Section}{Methods}
\describe{
\item[show] Use \code{show(cloutput-object)} for brief information
\item[ftable] Use \code{ftable(cloutput-object)} to obtain a confusion matrix/cross-tabulation
of \code{y} vs. \code{yhat}, s. \code{\LinkA{ftable,cloutput-method}{ftable,cloutput.Rdash.method}}.
\item[plot] Use \code{plot(cloutput-object)} to generate a probability plot of the matrix
\code{prob} described above, s. \code{\LinkA{plot,cloutput-method}{plot,cloutput.Rdash.method}}
\item[roc] Use \code{roc(cloutput-object)} to compute the empirical ROC curve and the
Area Under the Curve (AUC) based on the predicted probabilities, s.\code{\LinkA{roc,cloutput-method}{roc,cloutput.Rdash.method}}
}
\end{Section}
\begin{Author}\relax
Martin Slawski \email{martin.slawski@campus.lmu.de}

Anne-Laure Boulesteix \url{http://www.slcmsr.net/boulesteix}
\end{Author}
\begin{SeeAlso}\relax
\code{clvarseloutput}
\code{\LinkA{compBoostCMA}{compBoostCMA}}, \code{\LinkA{dldaCMA}{dldaCMA}}, \code{\LinkA{ElasticNetCMA}{ElasticNetCMA}},
\code{\LinkA{fdaCMA}{fdaCMA}}, \code{\LinkA{flexdaCMA}{flexdaCMA}}, \code{\LinkA{gbmCMA}{gbmCMA}},
\code{\LinkA{knnCMA}{knnCMA}}, \code{\LinkA{ldaCMA}{ldaCMA}}, \code{\LinkA{LassoCMA}{LassoCMA}},
\code{\LinkA{nnetCMA}{nnetCMA}}, \code{\LinkA{pknnCMA}{pknnCMA}}, \code{\LinkA{plrCMA}{plrCMA}},
\code{\LinkA{pls\_ldaCMA}{pls.Rul.ldaCMA}}, \code{\LinkA{pls\_lrCMA}{pls.Rul.lrCMA}}, \code{\LinkA{pls\_rfCMA}{pls.Rul.rfCMA}},
\code{\LinkA{pnnCMA}{pnnCMA}}, \code{\LinkA{qdaCMA}{qdaCMA}}, \code{\LinkA{rfCMA}{rfCMA}},
\code{\LinkA{scdaCMA}{scdaCMA}}, \code{\LinkA{shrinkldaCMA}{shrinkldaCMA}}, \code{\LinkA{svmCMA}{svmCMA}}
\end{SeeAlso}

