\HeaderA{pknnCMA-methods}{Probabilistic nearest neighbours}{pknnCMA.Rdash.methods}
\aliasA{pknnCMA,data.frame,missing,formula-method}{pknnCMA-methods}{pknnCMA,data.frame,missing,formula.Rdash.method}
\aliasA{pknnCMA,ExpressionSet,character,missing-method}{pknnCMA-methods}{pknnCMA,ExpressionSet,character,missing.Rdash.method}
\aliasA{pknnCMA,matrix,factor,missing-method}{pknnCMA-methods}{pknnCMA,matrix,factor,missing.Rdash.method}
\aliasA{pknnCMA,matrix,numeric,missing-method}{pknnCMA-methods}{pknnCMA,matrix,numeric,missing.Rdash.method}
\keyword{multivariate}{pknnCMA-methods}
\begin{Description}\relax
Nearest neighbour variant that replaces the simple
voting scheme by a weighted one (based on euclidean distances).
This is also used to compute class probabilities.
\end{Description}
\begin{Section}{Methods}
\describe{

\item[X = "matrix", y = "numeric", f = "missing"] signature 1

\item[X = "matrix", y = "factor", f = "missing"] signature 2

\item[X = "data.frame", y = "missing", f = "formula"] signature 3

\item[X = "ExpressionSet", y = "character", f = "missing"] signature 4
}
For further argument and output information, consult
\code{\LinkA{pknnCMA}{pknnCMA}.}
\end{Section}

