I have a classifier for a binary problem. That has outputs between 0 and 1 for predictions for the two class A or B (for example sunny, not sunny). The classifier has ran on 5 unique folds of the data set and in each fold I have the outcome of the classifier as a value between 0 and 1 for each class, Class A (for example 0.83) and Class B (0.17). I also know the true label for that classification attempt.
For each fold I also have Cohen's Kappa, Weighted Cross Entropy, confusion matrix, Precision, Recall and F1.
Is there anyway to calculate the AUC or approximate it using the data I have at hand?
Many thanks, Mo