perfcurve and ROC curve

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karlo gonzales
karlo gonzales on 23 Feb 2016
Commented: Ilya on 24 Feb 2016
Dear friends,
I have a confusion about ROC curve and hopefully you can help me!
To plot ROC, i was naively using a simple command as plot(False_alarm_rate,Hit_rate,'-'). But, it is not exactly the same as perfcurve plot. To use this function, i wrote the following script
Q=reshape([Hit_rate False_alarm_rate],[],1);
Labels=[]; Labels = ones(size(Q,1),1);
Labels(end/2+1:end) = 0;
PosClass = 1;
[X Y T,AUC] = perfcurve(Labels,Q,PosClass);
figure, plot(X,Y,'r') % ROC
could you please tell me , what i am missing here?
- BTW, can we calculate d-prime from output of perfcurve?
thanks in advance, Karlo

Answers (1)

Ilya on 23 Feb 2016
Q must be classification scores. What you put in Q sounds more like what perfcurve should return as output. Take a classifier from the Statistics and Machine Learning Toolbox such as decision tree, discriminant etc and look at the predict method. The second output from the predict method is classification score.
karlo gonzales
karlo gonzales on 23 Feb 2016
Thanks Ilya for your reply.
Indeed, Q represent the Hit rate and the False alarm rate for different subjects who performed a memory test. would you please tell me how you would plot ROC for this case?
Ilya on 24 Feb 2016
The standard ROC curve is a plot of TPR vs FPR. The doc for perfcurve defines TPR and FPR (as well as other criteria) in the name-value pair section. You could write down definitions of false alarm rate etc and see if you can transform those into TPR and FPR. I am sure you are at least as good as I am at algebra, and, unlike you, I do not know what hit rate and false alarm rate are.

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