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Narrowing the gap: expected versus deployment performance
3
Zitationen
5
Autoren
2023
Jahr
Abstract
Longitudinal partitioning methods, where models are tested on newer data than the development set, yielded the least optimism. Including older years in the training dataset did not degrade deployable model performance. Using all available data for model development fully leveraged longitudinal partitioning by measuring year-to-year performance.
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