Description Usage Arguments Details Value Examples
Function to compute the Area under the ROC Curve through precrec package.
1 2 3 | AUROC.single.class(labels, scores, folds = NULL, seed = NULL)
AUROC.single.over.classes(target, predicted, folds = NULL, seed = NULL)
|
labels |
vector of the true labels (0 negative, 1 positive examples). |
scores |
a numeric vector of the values of the predicted labels (scores). |
folds |
number of folds on which computing the AUROC. If |
seed |
initialization seed for the random generator to create folds. Set |
target |
annotation matrix: rows correspond to examples and columns to classes. target[i,j]=1 if example i belongs to class j, target[i,j]=0 otherwise. |
predicted |
a numeric matrix with predicted values (scores): rows correspond to examples and columns to classes. |
The AUROC (for a single class or for a set of classes) is computed either one-shot or averaged across stratified folds.
AUROC.single.class
computes the AUROC just for a given class.
AUROC.single.over.classes
computes the AUROC for a set of classes, including their average values across all the classes.
For all those classes having zero annotations, the AUROC is set to 0.5. These classes are included in the computing of the AUROC averaged across classes, both when the AUROC is computed one-shot or averaged across stratified folds.
The AUROC is set to 0.5 to all those classes having zero annotations.
Names of rows and columns of labels
and predicted
must be provided in the same order, otherwise a stop message is returned.
AUROC.single.class
returns a numeric value corresponding to the AUROC for the considered class;
AUPR.single.over.classes
returns a list with two elements:
average: the average AUROC across classes;
per.class: a named vector with AUROC for each class. Names correspond to classes.
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