ROC representation for the discriminability of multi-classification markers

DOI10.1016/j.patcog.2016.06.024zbMath1414.62285OpenAlexW2464967658MaRDI QIDQ2417831

Chin-Tsang Chiang, Yun-Jhong Wu

Publication date: 29 May 2019

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2016.06.024

zbMATH Keywords

hypervolumemanifoldutilityreceiver operating characteristicoptimal classificationdiscriminability

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Uses Software

• HUM

Cites Work

• ROC analysis with multiple classes and multiple tests: methodology and its application in microarray studies
• The ROC manifold for classification systems
• Statistical decision theory and Bayesian analysis. 2nd ed
• Non-parametric analysis of a generalized regression model. The maximum rank correlation estimator
• Generalization of the theory of signal detectability to \(n\)-event \(m\)-dimensional forced-choice tasks.
• Optimal receiver operating characteristic manifolds
• Multiple-event forced-choice tasks in the theory of signal detectability
• COMBINING MULTIPLE MARKERS FOR MULTI-CATEGORY CLASSIFICATION: AN ROC SURFACE APPROACH

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