= Prediction optimism
{title2=$\operatorname{Opt}=\operatorname{Err}_{\mathrm{in}}-\mathbb E\operatorname{err}$}
Prediction optimism is the difference between expected squared prediction error on new independent responses at the training covariates and expected <training error>. Reusing responses to fit and assess a model tends to make training error too favorable. The <covariance formula for prediction optimism> measures this reuse without assuming a linear fitting rule.
// Target: probability-and-statistics.bigb
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