Overfitting
/ˈoʊvərˌfɪtɪŋ/o·ver·fit·tingnoun
Definition
1.[in statistical learning] the failure mode in which a model absorbs noise particular to its training sample and therefore predicts unseen data worse than a simpler model would.
Validation error rose while training error kept falling — textbook overfitting.
Formal statement
E[(y - fhat(x))^2] = Bias[fhat]^2 + Var[fhat] + sigma^2Overfitting is the regime where the variance term dominates the decomposition.
Etymology
From over- 'excessively' plus fit, in the statistical sense of fitting a curve to points; in use in the regression literature from the mid-twentieth century.
Synonyms
- high variancesense 1 · Near
Antonyms
- underfittingsense 1 · Gradable