In binary classification, the average accuracy obtained on individual cross-validation folds is a problematic measure of generalization performance. First, it makes statistical inference difficult. Second, it leads to an optimistic estimate when a biased classifier is tested on an imbalanced dataset. Both problems can be overcome by replacing the conventional point estimate of accuracy by an estimate of the posterior distribution of the balanced accuracy.
This archive contains a set of MATLAB functions to estimate the posterior distribution of the balanced accuracy and compute its associated statistics.
For full details, see:
K.H. Brodersen, C.S. Ong, K.E. Stephan, J.M. Buhmann (2010)
The balanced accuracy and its posterior distribution.
Proceedings of the 20th International Conference on Pattern Recognition, 3121-3124.