Object to encapsulate numerical predictions together with the corresponding true class labels, optionally collecting predictions and labels for several cross-validation or bootstrapping runs.

Objects can be created by using the
`prediction`

function.

`predictions`

:A list, in which each element is a vector of predictions (the list has length > 1 for x-validation data.)

`labels`

:Analogously, a list in which each element is a vector of true class labels.

`cutoffs`

:A list in which each element is a vector of all necessary cutoffs. Each cutoff vector consists of the predicted scores (duplicates removed), in descending order.

`fp`

:A list in which each element is a vector of the number (not the rate!) of false positives induced by the cutoffs given in the corresponding 'cutoffs' list entry.

`tp`

:As fp, but for true positives.

`tn`

:As fp, but for true negatives.

`fn`

:As fp, but for false negatives.

`n.pos`

:A list in which each element contains the number of positive samples in the given x-validation run.

`n.neg`

:As n.pos, but for negative samples.

`n.pos.pred`

:A list in which each element is a vector of the number of samples predicted as positive at the cutoffs given in the corresponding 'cutoffs' entry.

`n.neg.pred`

:As n.pos.pred, but for negatively predicted samples.

A detailed list of references can be found on the ROCR homepage at http://rocr.bioinf.mpi-sb.mpg.de.

`prediction`

, `performance`

,
`performance-class`

, `plot.performance`