Estimation and Applications of Quantiles in Deep Binary Classification
IEEE Transactions on Artificial Intelligence(2022)
Abstract
Conditional quantiles obtained via regression are used as a robust alternative to classical conditional means in econometrics and statistics, as they can capture the uncertainty in a prediction, and model tail behaviors, while making very few distributional assumptions. In this work, we extend the notion of conditional quantiles to the binary classification setting—allowing us to quantify the unce...
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Key words
Artificial intelligence,Uncertainty,Predictive models,Deep learning,Computational modeling,Task analysis,Robustness
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