% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getConfMatrix.R
\name{getConfMatrix}
\alias{getConfMatrix}
\title{Confusion matrix.}
\usage{
getConfMatrix(pred, relative = FALSE)
}
\arguments{
\item{pred}{[\code{\link{Prediction}}]\cr
Prediction object.}

\item{relative}{[\code{logical(1)}]\cr
If \code{TRUE} rows are normalized to show relative frequencies.
Default is \code{FALSE}.}
}
\value{
[\code{matrix}]. A confusion matrix.
}
\description{
\code{getConfMatrix} is deprecated. Please use \code{\link{calculateConfusionMatrix}}.


Calculates confusion matrix for (possibly resampled) prediction.
Rows indicate true classes, columns predicted classes.

The marginal elements count the number of classification
errors for the respective row or column, i.e., the number of errors
when you condition on the corresponding true (rows) or predicted
(columns) class. The last element in the margin diagonal
displays the total amount of errors.

Note that for resampling no further aggregation is currently performed.
All predictions on all test sets are joined to a vector yhat, as are all labels
joined to a vector y. Then yhat is simply tabulated vs y, as if both were computed on
a single test set. This probably mainly makes sense when cross-validation is used for resampling.
}
\seealso{
\code{\link{predict.WrappedModel}}
}
