Active learning in automated text classification: a case study exploring bias in predicted model performance metrics - Varghese, Arun; Hong, Tao; Hunter, Chelsea; Agyeman-Badu, George; Cawley, Michelle (Environment systems & decisions, 2019)
Keywords: Active learning; Arsenic; Artificial intelligence; automation; Bias; Business metrics; case studies; Computer simulation; Control; cost effectiveness; data collection; Datasets; Earth and Environmental Science; Environment; Environmental Management; experts; health effects assessments; Health risks; human health; Innovations; Learning algorithms; Literature reviews; Machine learning; Mathematical models; Model accuracy; model validation; multidisciplinary; Organic chemistry; Performance measurement; Performance prediction; prediction; Quality Control; Random sampling; Reliability; Risk assessment; Safety and Risk; Science; Statistical analysis; Statistical sampling; Systems Theory; Toxicology; Training; Literature review; Systematic review; Natural language processing; Automated document classification; Active learning; Machine learning