Optimal thresholds criteria for ROC surfaces
نویسندگان
چکیده
منابع مشابه
Optimal thresholds criteria for ROC surfaces
Consider the ROC surface which is a generalization of the ROC curve for three−class diagnostic problems. In this work, we propose five criteria for the three−class ROC surface by extending the Youden index, the sum of sensitivity and specificity, the maximum vertical distance, the amended closest-to-(0,1) and the true rate. It may be concluded that these five criteria can be expressed as a func...
متن کاملVisualisation of multi-class ROC surfaces
The Receiver Operating Characteristic (ROC) has become a standard tool for the analysis and comparison of binary classifiers when the costs of misclassification are unknown. Although there has been relatively little work in examining ROC for more than two classes – there has been growing interest in the area, and in recent studies we have formulated it in terms of misclassification rates. Altho...
متن کامل1565Identifying Optimal HIV Viral Load (VL) Thresholds for Predicting Antiretroviral Treatment Failure (TF) Using ROC Curve Analysis
Background. Guidelines on HIV treatment differ in recommended VL thresholds indicative of TF. Improvements in VL assay sensitivity and worldwide scale-up of VL monitoring make it increasingly important to determine optimal VLs thresholds for guiding treatment changes. Receiver operating characteristic (ROC) curves can identify optimal VL thresholds which maximize sensitivity and specificity for...
متن کاملNew Algorithms for Optimizing Multi-Class Classifiers via ROC Surfaces
We study the problem of optimizing a multiclass classifier based on its ROC hypersurface and a matrix describing the costs of each type of prediction error. For a binary classifier, it is straightforward to find an optimal operating point based on its ROC curve and the relative cost of true positive to false positive error. However, the corresponding multiclass problem (finding an optimal opera...
متن کاملOn optimal reject rules and ROC curves
In this paper we make the connection between two approaches for supervised classification with a rejection option. The first approach is due to Tortorella and is based on ROC curves and the second is a generalisation of Chow s optimal rule. 2004 Elsevier B.V. All rights reserved.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Korean Data and Information Science Society
سال: 2013
ISSN: 1598-9402
DOI: 10.7465/jkdi.2013.24.6.1489