Bias-variance tradeoff

Error splits into being systematically wrong because the model is too simple, and being unstable because it follows the particular sample it saw. Reducing one usually raises the other.

A definition is not an understanding. This is taught properly in Memorising instead of learning, part of Overfitting & regularisation.

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Terms from the same topic

OverfittingUnderfittingRegularisationDropoutEarly stoppingHeld-out setTrain/validation/test splitCross-validation