confusionmatStats(g​roup,grouphat)

This function evaluates the common performance measures for classification models.

function stats = confusionmatStats(group,grouphat)
% INPUT
% group = true class labels
% grouphat = predicted class labels
%
% OR INPUT
% stats = confusionmatStats(group);
% group = confusion matrix from matlab function (confusionmat)
%
% OUTPUT
% stats is a structure array
% stats.confusionMat
% Predicted Classes
% p' n'
% ___|_____|_____|
% Actual p | | |
% Classes n | | |
%
% stats.accuracy = (TP + TN)/(TP + FP + FN + TN) ; the average accuracy is returned
% stats.precision = TP / (TP + FP) % for each class label
% stats.sensitivity = TP / (TP + FN) % for each class label
% stats.specificity = TN / (FP + TN) % for each class label
% stats.recall = sensitivity % for each class label
% stats.F-score = 2*TP /(2*TP + FP + FN) % for each class label
%
% TP: true positive, TN: true negative,
% FP: false positive, FN: false negative
%