Graham W. Taylor

Using Set Learning to Improve Set-Valued Classifiers on Long-tailed Data

Set-valued classification (SVC) offers a practical approach to communicating uncertainty while maintaining accuracy by predicting variable-sized sets per input rather than fixed-sized sets (e.g. top-1 or top-5). However, set-valued classifiers (SVCs) exhibit significantly degraded performance on long-tailed and imbalan...