Predicting sample size required for classification performance - Figueroa, Rosa L; Zeng-Treitler, Qing; Kandula, Sasikiran; Ngo, Long H (BMC medical informatics and decision making, 2012)
Keywords: Algorithms; Classification; Confidence intervals; Data Interpretation, Statistical; Data processing; Decision making; Diagnosis, Computer-Assisted; Experiments; Health Informatics; Humans; Informatics; Information Systems and Communication Service; Learning; Learning algorithms; Learning Curve; Machine learning; Management; Management of Computing and Information Systems; Medical records; Medical research; Medicine; Medicine & Public Health; Methods; Models, Statistical; Nonlinear Dynamics; Pattern Recognition, Automated; Predictive Value of Tests; Probability Learning; Problem-Based Learning - methods; Reproducibility of Results; Research Article; Sample Size; Sampling; Stochastic Processes; Studies; United States; Learning Curve; Mean Absolute Error; Annotate Data; Root Mean Square Error; Active Learning