Robust penalized logistic regression with truncated loss functions

DOI10.1002/cjs.10105zbMath1219.62105OpenAlexW1973650202WikidataQ35599481 ScholiaQ35599481MaRDI QIDQ3087592

Yu Feng Liu, Seo Young Park

Publication date: 16 August 2011

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3233197

zbMATH Keywords

classificationrobustnesstruncationprobability estimation

Mathematics Subject Classification ID

Related Items (9)

Robust relevance vector machine for classification with variational inference ⋮ A robust outlier control framework for classification designed with family of homotopy loss function ⋮ Robust logistic regression with shift parameter estimation ⋮ Robust Support Vector Machines for Classification with Nonconvex and Smooth Losses ⋮ Unnamed Item ⋮ Quadratic Majorization for Nonconvex Loss with Applications to the Boosting Algorithm ⋮ Robust boosting with truncated loss functions ⋮ Maximum likelihood optimal and robust support vector regression with \textit{lncosh} loss function ⋮ Robust logistic regression modelling via the elastic net-type regularization and tuning parameter selection

Uses Software

• gss

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