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Leveraging Uncertainty Estimates To Improve Classifier Performance
Binary classification involves predicting the label of an instance based on whether the model score for the positive class exceeds a threshold chosen based on the application requirements (e. g., maximizing recall for a precision bound).
Interpretability of Epidemiological Models : The Curse of Non-Identifiability
Interpretability of epidemiological models is a key consideration, especially when these models are used in a public health setting.
COVID-19: Strategies for Allocation of Test Kits
Thus, it is important to allocate a separate budget of test-kits per day targeted towards preventing community spread and detecting new cases early on.
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