ml

🟠 Repeat: Bias-Variance Diagnostic

You see... It's... You do...
Both train and test error high High bias (underfitting) More complex model, add features
Low train, high test error High variance (overfitting) More data, regularize, simplify
Both low and close Just right Ship it