How to calculate AUC of ROC curve from these data ?

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Pradya Panyainkaew
Pradya Panyainkaew 2018-4-22
回答： Sharmili S 2023-1-27
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
  1 个评论
Victor Daniel Reyes Dreke
Victor Daniel Reyes Dreke 2020-5-18
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

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回答（1 个）

Sharmili S
Sharmili S 2023-1-27
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

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