2 papers
cs.LG2026
Classifier Pooling for Modern Ordinal Classification
Noam H. Rotenberg, Andreia V. Faria, Brian Caffo
Ordinal data is widely prevalent in clinical and other domains, yet there is a lack of both modern, machine-learning based methods and publicly available software to address it. In…
cs.LG2026
Adaptive Label Error Detection: A Bayesian Approach to Mislabeled Data Detection
Zan Chaudhry, Noam H. Rotenberg, Brian Caffo +2
Machine learning classification systems are susceptible to poor performance when trained with incorrect ground truth labels, even when data is well-curated by expert annotators. As…