Grouped Variable Selection Using Area under the ROC with Imbalanced Data

DOI10.1080/03610918.2013.818691zbMath1419.62176OpenAlexW2034884560MaRDI QIDQ3178533

Yichen Qin, Shuangge Ma, Yang Li, Jiaxu Chen, Li-Min Wang

Publication date: 14 July 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2013.818691

zbMATH Keywords

group Lassoimbalanced dataarea under ROCtrue positive rate

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Cites Work

• Cost-sensitive boosting for classification of imbalanced data
• The Group Lasso for Logistic Regression
• A group bridge approach for variable selection
• Model Selection and Estimation in Regression with Grouped Variables
• Combining Multiple Markers for Classification Using ROC
• Combining Predictors for Classification Using the Area under the Receiver Operating Characteristic Curve

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