How to calculate AUC of ROC curve from these data ?

Hi everyone I have my raw data that I attach in this question.These data are output from a neural network classification and I am able to plot ROC curve from them. by the code below;

figure(1)
plotroc(targets_train,outputs_train)
title({'ROC Curve of Train Set for Neural network classification'})
xlabel('False positive rate') % x-axis label
ylabel('True positive rate') % y-axis label
figure(2)
plotroc(targets_testset,outputs_test)
title({'ROC Curve of Test Set for Neural network classification'})
xlabel('False positive rate') % x-axis label
ylabel('True positive rate') % y-axis label

However, I don't have any idea, how to calculate AUC of ROC curve from these data ?.

Anyone help me,please ?

Thanks in advance

Pradya

[Victor Daniel Reyes Dreke]

Try to use the function [tpr,fpr]=roc(targets,outputs). This function outcomes are the true positive rate and false positive rate used to build the ROC Curve. Finally, trapz(fpr,tpr) will give you the area under the ROC curve

Answer 1

[Sharmili S]

figure(1)

plotroc(targets_train,outputs_train)

title({'ROC Curve of Train Set for Neural network classification'})

xlabel('False positive rate') % x-axis label

ylabel('True positive rate') % y-axis label

figure(2)

plotroc(targets_testset,outputs_test)

title({'ROC Curve of Test Set for Neural network classification'})

xlabel('False positive rate') % x-axis label

ylabel('True positive rate') % y-axis label