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stat.ML2025
Inequalities for Optimization of Classification Algorithms: A Perspective Motivated by Diagnostic Testing
Paul N. Patrone, Anthony J. Kearsley
Motivated by canonical problems in medical diagnostics, we propose and study properties of an objective function that uniformly bounds uncertainties in quantities of interest extra…
stat.ML2024
Analysis of Diagnostics (Part II): Prevalence, Linear Independence, and Unsupervised Learning
Paul N. Patrone, Raquel A. Binder, Catherine S. Forconi +2
This is the second manuscript in a two-part series that uses diagnostic testing to understand the connection between prevalence (i.e. number of elements in a class), uncertainty qu…
stat.ML2024
Analysis of Diagnostics (Part I): Prevalence, Uncertainty Quantification, and Machine Learning
Paul N. Patrone, Raquel A. Binder, Catherine S. Forconi +2
Diagnostic testing provides a unique setting for studying and developing tools in classification theory. In such contexts, the concept of prevalence, i.e. the number of individuals…