MATLAB实现ROC曲线程序源码.zip

function [auc, curve] = ROC(score, target, Lp, Ln) % This function is to calculat the ordinats of points of ROC curve and the area % under ROC curve(AUC). % This program was described in Fawcett's paper "ROC Graphs: notes and practical % considerations for researchers". % % Output: % curve: N*3 matrix. % the 1st column is FP % the 2nd column is TP % the 3rd column is score % note: the last row, etc.the last point is [1,1,0]. if output of this % function is applied to roc_av.m to calculate average curve of roc, % it should be delete % auc: scale number, area under ROC curve. % % Input parameters: % score: output of classifier. high socre denote the pattern is more likely % to be POSITIVE pattern. % target: classlabel of each pattern. % Lp: label of POSITIVE pattern. % Ln: label of NEGATIVE pattern. % % % QingRen (qingren_ny#126.com) % 2006-7-20 % len = length(score); % number of patterns if len ~= length(target) error('The length of tow input vectors should be equal\n'); end P = 0; % number of Positive pattern N = 0; % number of Negative pattern for i = 1:len if target(i) == Lp P = P + 1; elseif target(i) == Ln N = N + 1; else error('Wrong target value'); end end % sort "L" in decending order by scores score = score(:); target = target(:); L = [score target]; L = sortrows(L,1); index = len:-1:1; index = index'; %' L = L(index,:); fp = 0; fp_pre = 0; % number of False Positive pattern tp = 0; tp_pre = 0; % number of True Positive pattern. score_pre = -10000; curve = []; auc = 0; for i = 1:len if L(i,1) ~= score_pre curve = [curve; [fp/N, tp/P, L(i,1)]]; auc = auc + trapezoid(fp, fp_pre, tp, tp_pre); score_pre = L(i,1); fp_pre = fp; tp_pre = tp; end if L(i,2) == Lp tp = tp + 1; else fp = fp + 1; end end curve = [curve; [1,1,0]]; auc = auc / P / N; auc = auc + trapezoid(1, fp_pre/N, 1, tp_pre/P); % calculat the area of trapezoid function area = trapezoid(x1,x2,y1,y2) a = abs(x1-x2); b = abs(y1+y2); area = a * b / 2;