Least Ambiguous Set-Valued Classifiers With Bounded Error Levels

DOI10.1080/01621459.2017.1395341zbMath1478.62175arXiv1609.00451OpenAlexW2514278201MaRDI QIDQ5229906

Jing Lei, Mauricio Sadinle, Larry Alan Wasserman

Publication date: 19 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1609.00451

zbMATH Keywords

Bayes classifiermulticlass classificationreject optionambiguous observationnondeterministic classifieroracle classifier

Mathematics Subject Classification ID

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

Related Items

Conformal Prediction: A Gentle Introduction, Criteria of efficiency for set-valued classification, Selective Prediction-Set Models with Coverage Rate Guarantees, Unnamed Item, Distribution-Free Prediction Sets for Two-Layer Hierarchical Models, Three-way decision and conformal prediction: isomorphisms, differences and theoretical properties of cautious learning approaches, Nested conformal prediction sets for classification with applications to probation data, Set-Valued Support Vector Machine with Bounded Error Rates, Is distribution-free inference possible for binary regression?, Minimax semi-supervised set-valued approach to multi-class classification, Optimal rates for nonparametric F-score binary classification via post-processing, Agnostic tests can control the type I and type II errors simultaneously, On soft computing with random fuzzy sets in econometrics and machine learning

Uses Software

• UCI-ml
• ML-KNN

Cites Work

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