Abstract
Three (3) different methods (logistic regression, covariate shift and k-NN) were applied to five (5) internal datasets and one (1) external, publically available dataset where covariate shift existed. In all cases, k-NN’s performance was inferior to either logistic regression or covariate shift. Surprisingly, there was no obvious advantage for using covariate shift to reweight the training data in the examined datasets.
Cite
CITATION STYLE
APA
McGaughey, G., Walters, W. P., & Goldman, B. (2016). Understanding covariate shift in model performance. F1000Research, 5, 597. https://doi.org/10.12688/f1000research.8317.3
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