![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/192743/image.png)
I want to plot the Roc curve using perfcurve function i have 2 plot which code is right
6 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Salma Hassan
am 27 Jul. 2018
Kommentiert: KALYAN ACHARJYA
am 30 Jul. 2018
the code is [Xpr,Ypr,Tpr,AUCpr] = perfcurve(targets,abs(scores(:,1)), 1, 'xCrit', 'reca', 'yCrit', 'fpr');
plot(Xpr,Ypr)
xlabel('specificity'); ylabel('sensitivity') title(['ROC curve (AUC: ' num2str(AUCpr) ')'])
where scores(2 columns ) the first for predict abnormal image and the second for normal the problem is i got this graph
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/192720/image.png)
and if i change the score into abs(scores(:,2)), 1,i get an extremely different graph
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/192721/image.png)
0 Kommentare
Akzeptierte Antwort
KALYAN ACHARJYA
am 29 Jul. 2018
Bearbeitet: KALYAN ACHARJYA
am 29 Jul. 2018
Let me clear that ROC curve: 1-specificity vs sensitivity (In your figure x-axis is specificity). Ant the traditional ROC curve looks like as second figure. First one is incorrect. If your curve position towards the northwest corner, it is more accurate. Better follow TOM paper , here explains everything.
Attache figure for some sample ROC curves. AUC value range from 0.5-0.99,AUC value in larger side more better the proposed method. Curve never appper below the reference line (In attached figure red line).Purple curve having better method.
![](https://www.mathworks.com/matlabcentral/answers/uploaded_files/192743/image.png)
Hope the answer helps you!
Cheers!
2 Kommentare
KALYAN ACHARJYA
am 30 Jul. 2018
Just reference line, worst condition (50% random probability ), your ROC curve on that line.
Weitere Antworten (0)
Siehe auch
Kategorien
Mehr zu ROC - AUC finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!