Results 11 to 20 of about 359,159 (253)
Concentration and ROC Curves, Revisited [PDF]
Sankhya A, 2021 AbstractThis work is aimed at illustrating the strict relationship between a general definition of concentration function appeared quite some time ago on this journal and a widely used measure of the diagnostic strength of a family of binary classifiers indexed by a threshold parameter, the so-called ROC curve.
Gasparini M., Sacchetto L.
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Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
Risks, 2022 In the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying
Błażej Kochański
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Entropy, 2020 Background: This investigation included both a study of potential non-invasive diagnostic approaches for the bladder cancer biomarker UBC® Rapid Test and a study including comparative methods about sensitivity–specificity characteristic (SS-ROC) and ...
Peter Oehr, Thorsten Ecke
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Validation of the highly sensitive person scale for suicide screening in high-risk groups: A case-control study [PDF]
Precision and Future Medicine, 2023 Purpose High sensitivity is among the risk factors that increase psychological burden, increasing the risk of suicide in some people. The aim of the study was to develop a Korean version of the Highly Sensitive Person (HSP) scale and investigate its ...
Yaehee Cho +5 more
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Induction Motor Fault Classification Based on ROC Curve and t-SNE
IEEE Access, 2021 This paper proposes a novel fault classification method with application to induction motors, which is based on integrating and combining with receiver operating characteristic (ROC) curve and t-distribution stochastic neighbor embedding (t-SNE ...
Chun-Yao Lee, Wen-Cheng Lin
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Lognormal Lorenz and normal receiver operating characteristic curves as mirror images [PDF]
Royal Society Open Science, 2015 The Lorenz curve for assessing economic inequality depicts the relation between two cumulative distribution functions (CDFs), one for the distribution of incomes or wealth and the other for their first-moment distribution.
R. John Irwin, Michael J. Hautus
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ROC curves in cost space [PDF]
Machine Learning, 2013 ROC curves and cost curves are two popular ways of visualising classifier performance, finding appropriate thresholds according to the operating condition, and deriving useful aggregated measures such as the area under the ROC curve (AUC) or the area under the optimal cost curve.
José Hernández-Orallo +2 more
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ROC curves for regression [PDF]
Pattern Recognition, 2013 I would like to thank Peter Flach and Nicolas Lachiche for some very useful comments and corrections on earlier versions of this paper, especially the suggestion of drawing normalised curves (dividing x-axis and y-axis by n). This work was supported by the MEC/MINECO projects CONSOLIDER-INGENIO CSD2007-00022 and TIN 2010-21062-C02-02, GVA project ...
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Web-Bootstrap Estimate of Area Under ROC Curve
Austrian Journal of Statistics, 2016 The accuracy of binary discrimination models (discrimination between cases with and without any condition) is usually summarized by classification matrix (also called a confusion, assignment, or prediction matrix). Receiver operating characteristic (ROC)
Hana Skalská, Václav Freylich
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Receiver operating characteristic curve: overview and practical use for clinicians [PDF]
Korean Journal of Anesthesiology, 2022 Using diagnostic testing to determine the presence or absence of a disease is essential in clinical practice. In many cases, test results are obtained as continuous values and require a process of conversion and interpretation and into a dichotomous form
Francis Sahngun Nahm
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