Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content
Fig. 10 | BMC Medical Informatics and Decision Making

Fig. 10

From: A novel estimator for the two-way partial AUC

Fig. 10

Real data illustrations. Panel a compares the ROC curves generated from the predictions of a logistic regression and a random forest classifier on the Diabetic Retinopathy Debrecen dataset, while panel b presents the analogous comparison on the Sepsis Survival dataset. In both panels the red square captures the area of interest of the ROC space obtained by setting the sensitivity and specificity thresholds to \(b_{se} = 0.4\) and \(b_{sp} = 0.4\), respectively

Back to article page

BMC Medical Informatics and Decision Making

ISSN: 1472-6947

Contact us