A New Look at the Statistical Model Identification.¶
Akaike, H. (1974). A New Look at the Statistical Model Identification. IEEE, 19(6), 716-723.
Cited by¶
3 citations across 3 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Overfitting
This sourceAIC model selection criterion, information-theoretic approach to overfitting.
- Parsimony (Occam's Razor)
- … praeter necessitatem" (entities are not to be multiplied beyond necessity) codified the maxim and supplied the foundational name; modern formalizations ground parsimony in Bayesian model comparison (marginal likelihood penalizes complexity automatically), information-theoretic criteria (Akaike Information Criterion
This sourceAIC model selection criterion, information-theoretic approach to overfitting.
- … praeter necessitatem" (entities are not to be multiplied beyond necessity) codified the maxim and supplied the foundational name; modern formalizations ground parsimony in Bayesian model comparison (marginal likelihood penalizes complexity automatically), information-theoretic criteria (Akaike Information Criterion
Mechanisms¶
- Candidate-Family Comparison Grid
- Its failure mode is information-criterion absolutism — collapsing the whole grid to a single number and letting, say, the Akaike Information Criterion crown a winner.
This sourceDefines AIC and selects the competing model attaining the minimum criterion value.
- Its failure mode is information-criterion absolutism — collapsing the whole grid to a single number and letting, say, the Akaike Information Criterion crown a winner.
Verification¶
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