Function colAUC calculates Area under ROC curve (AUC) for a vector or for
each column of a matrix.
The main properties of this code:
* Ability to work with multi-dimensional data.
* Ability to work with multi-class datasets.
* Speed - this code was written to calculate AUC's for large number of
features, fast.
* Two different algorithms are provided one based on integrating ROC
curves and one based on Wilcoxon Rank Sum Test aka. Mann-Whitney U Test.
* Function can be used to plot ROC curves.
I'm sorry but it is not clear how to get multiclass auc if I have Y as the true label of 1...c classes and Yest as 1...c column vector with predictive score for each instance belong to certain class. The output auc is a c x c x(c-1)/2 combination in your case, take mean(auc) returns c auc values.
I would remove the absolute computation: ( auc = 0.5 + abs(0.5-auc);) as it is indicative of the effect direction which is necessary for most statistical analyses.