\Header{pamr.confusion}{A function giving a table of true versus predicted values,
from a nearest shrunken centroid fit.}
\begin{Description}\relax
A function giving a table of true versus predicted values,
from a nearest shrunken centroid fit.
\end{Description}
\begin{Usage}
\begin{verbatim}
pamr.confusion(fit, threshold, extra=TRUE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{fit}] The result of a call to pamr.train or pamr.cv
\item[\code{threshold}] The desired threshold value
\item[\code{extra}] If TRUE, class confusion rates are also computed
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
\code{pamr.confusion} Gives a cross-tabulation of true versus
predicted classes for the fit returned by pamr.train or pamr.cv,
at the specified threshold.
\end{Details}
\begin{Author}\relax
Trevor Hastie, Robert Tibshirani, Balasubramanian Narasimhan, and Gilbert Chu
\end{Author}
\begin{References}\relax
\end{References}
\begin{Examples}
\begin{ExampleCode}
set.seed(120)
x <- matrix(rnorm(1000*20),ncol=20)
y <- sample(c(1:4),size=20,replace=TRUE)
mydata <- list(x=x,y=y)
mytrain <-   pamr.train(mydata)
mycv <- pamr.cv(mytrain,mydata)
pamr.confusion(mytrain,  threshold=2)
pamr.confusion(mycv,  threshold=2)
 
\end{ExampleCode}
\end{Examples}

