quality:corruption, linguistic:paraphrasing, linguistic:voice_change, information:filtering
Statistical inference

Overfitted models... are often free of bias in the parameter estimators, but have estimated (and actual) sampling variances that are needlessly large (the precision of the estimators is poor, relative to what could have been accomplished with a more parsimonious model). False treatment effects tend to be identified, and false variables are included with overfitted models.... A best approximating model is achieved by properly balancing the errors of underfitting and overfitting.