matlab画ROC曲线

% predict - 分类器对测试集的分类结果 % ground_truth - 测试集的正确标签,这里只考虑二分类，即0和1 % auc - 返回ROC曲线的曲线下的面积 function plot_roc() %初始点为（1.0, 1.0） %计算出ground_truth中正样本的数目pos_num和负样本的数目neg_num % predict, ground_truth tic data = xlsread('F:\滑坡\洪都拉斯\多元线性回归数据20170715\ROC_DATA.xlsx'); predict = data(:,2); ground_truth = data(:,1); pos_num = sum(ground_truth==1); neg_num = sum(ground_truth==0); m=size(ground_truth,1); [pre,Index]=sort(predict); ground_truth=ground_truth(Index); x=zeros(m+1,1); y=zeros(m+1,1); auc=0; x(1)=1;y(1)=1; for i=2:m TP=sum(ground_truth(i:m)==1);FP=sum(ground_truth(i:m)==0); x(i)=FP/neg_num; y(i)=TP/pos_num; auc=auc+(y(i)+y(i-1))*(x(i-1)-x(i))/2; end; x(m+1)=0;y(m+1)=0; auc=auc+y(m)*x(m)/2;%计算的面积 disp('AUC : ') disp(auc) %% plot%% figure plot(x,y,'r','linewidth',1); hold on plot([0,1],[0,1]) grid on set(gca,'XTick',0:0.2:1); set(gca,'YTick',0:0.2:1); axis equal title('ROC Curve'); xlabel('1 - Specificity'); ylabel('Sensitivity'); set(gca, 'Fontname', 'arial'); grid on toc end %% Writed by 王明文 8/29/2017