COMBINING MULTIPLE MARKERS FOR MULTI-CATEGORY CLASSIFICATION: AN ROC SURFACE APPROACH

DOI10.1111/j.1467-842X.2011.00603.xzbMath1335.62111MaRDI QIDQ2802750

Yanyu Zhang, Jia-Liang Li

Publication date: 27 April 2016

Published in: Australian & New Zealand Journal of Statistics (Search for Journal in Brave)

zbMATH Keywords

bootstrapvolume under the ROC surfacemulti-category classificationmaximum rank correlation estimatorhypervolume under the ROC manifold

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Diagnostics, and linear inference and regression (62J20)

Related Items (8)

Multi-category diagnostic accuracy based on logistic regression ⋮ Using Adjacent-category Logits Procedure for Estimating Receiver Operating Characteristic Surface ⋮ On ROC analysis with nonbinary reference standard ⋮ ROC representation for the discriminability of multi-classification markers ⋮ A regression approach to ROC surface, with applications to Alzheimer's disease ⋮ Black-box optimization on hyper-rectangle using recursive modified pattern search and application to ROC-based classification problem ⋮ Comparison of three‐dimensional ROC surfaces for clustered and correlated markers, with a proteomics application ⋮ The generalized Lehmann ROC curves: Lehmann family of ROC surfaces

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• Approximation Theorems of Mathematical Statistics
• Linear Combinations of Multiple Diagnostic Markers
• Combining diagnostic test results to increase accuracy
• The Limiting Distribution of the Maximum Rank Correlation Estimator

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