\HeaderA{stamEval-class}{Results of a Complete StAM Analysis}{stamEval.Rdash.class}
\aliasA{initialize,stamEval-method}{stamEval-class}{initialize,stamEval.Rdash.method}
\aliasA{writeHTML,stamEval-method}{stamEval-class}{writeHTML,stamEval.Rdash.method}
\keyword{classes}{stamEval-class}
\begin{Description}\relax
Objects of this class are returned by \code{ctam.evaluate}. Results of all steps in a 
structured analysis of microarray data are stored.
\end{Description}
\begin{Section}{Objects from the Class}
Objects can be created by calls of the form 
\code{new("stamEval", exprs, cv, fit, pred, testset)}, but using \code{stam.evaluate} 
is recommended.
\end{Section}
\begin{Section}{Slots}
\describe{
\item[\code{chip}:] Object of class \code{"character"}, the name of the chip for 
which the classifier net is generated.
\item[\code{exprs}:] Object of class \code{"matrix"}, the plain matrix of 
expression levels [probesets x samples], rownames and colnames are expected to be 
defined
\item[\code{cv}:] Object of class \code{"stamCV"}, store cross validation results
\item[\code{fit}:] Object of class \code{"stamFit"}, store model fit
\item[\code{pred}:] Object of class \code{"stamPrediction"}, store 
prediction results
\item[\code{testset}:] Object of class \code{"numeric"}, indices of samples treated 
as test set. The others are used for trainig.
}
\end{Section}
\begin{Section}{Methods}
\describe{
\item[writeHTML] \code{signature(x = "stamEval")}: generate HTML information on a 
complete StAM analysis, but using \code{stam.writeHTML} is recommended.
}
\end{Section}
\begin{Author}\relax
Claudio Lottaz
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{stam.evaluate}{stam.evaluate}}, \code{\LinkA{stamCV-class}{stamCV.Rdash.class}}, 
\code{\LinkA{stamFit-class}{stamFit.Rdash.class}}, \code{\LinkA{stamPrediction-class}{stamPrediction.Rdash.class}}, 
\code{\LinkA{stam.writeHTML}{stam.writeHTML}}
\end{SeeAlso}

