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stat.ML2025
Localized Uncertainty Quantification in Random Forests via Proximities
Jake S. Rhodes, Scott D. Brown, J. Riley Wilkinson
In machine learning, uncertainty quantification helps assess the reliability of model predictions, which is important in high-stakes scenarios. Traditional approaches often emphasi…
stat.ML2025
Label-Guided Imputation via Forest-Based Proximities for Improved Time Series Classification
Jake S. Rhodes, Adam G. Rustad, Sofia Pelagalli Maia +5
Missing data is a common problem in time series data. Most methods for imputation ignore label information pertaining to the time series even if that information exists. In this pa…