Understanding covariate shift in model performance
نویسندگان
چکیده
منابع مشابه
Understanding covariate shift in model performance
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...
متن کاملUnderstanding covariate shift in model performance [ version
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...
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A common assumption in supervised learning is that the training and test input points follow the same probability distribution. However, this assumption is not fulfilled, e.g., in interpolation, extrapolation, or active learning scenarios. The violation of this assumption— known as the covariate shift—causes a heavy bias in standard generalization error estimation schemes such as cross-validati...
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ژورنال
عنوان ژورنال: F1000Research
سال: 2016
ISSN: 2046-1402
DOI: 10.12688/f1000research.8317.2