A set of MATLAB functions for evaluating generalization performance in binary classification.
bacc_med(C)
% Median of the balanced accuracy (i.e., the median of the average of
% two random variables that are independently distributed according to Beta
% distributions.)
%
% Usage:
% b_med = bacc_med(C)
%
% Arguments:
% C - 2x2 confusion matrix of classification outcomes. This matrix
% needs to be of the form C = [a b; c d] where
% <a> is the number of true positives
% <b> is the number of false negatives
% <c> is the number of false positives
% <d> is the number of true negatives
% In other words: rows are true classes, columns are estimated
% classes.
%
% Literature:
% K.H. Brodersen, C.S. Ong, K.E. Stephan, J.M. Buhmann (2010).
% The balanced accuracy and its posterior distribution. In: Proceedings
% of the 20th International Conference on Pattern Recognition.
% Kay H. Brodersen, ETH Zurich, Switzerland
% http://people.inf.ethz.ch/bkay/
% $Id: bacc_med.m 8245 2010-10-22 12:57:51Z bkay $
% -------------------------------------------------------------------------
function b_med = bacc_med(C)
% Get alphas and betas
A1 = C(1,1) + 1;
B1 = C(1,2) + 1;
A2 = C(2,2) + 1;
B2 = C(2,1) + 1;
% Compute median
b_med = betaavginv(0.5, A1, B1, A2, B2);
end