getConfMatrix is deprecated. Please use 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.

getConfMatrix(pred, relative = FALSE)

## Arguments

pred (Prediction) Prediction object. (logical(1)) If TRUE rows are normalized to show relative frequencies. Default is FALSE.

## Value

(matrix). A confusion matrix.