Abstract
Abstract This article offers a synthesis of Bayesian and sample-reuse approaches to the problem of high structure model selection geared to prediction. Similar methods are used for low structure models. Nested and nonnested paradigms are discussed and examples given.
Keywords
Model selectionSelection (genetic algorithm)Computer scienceNested set modelReuseBayesian probabilityMachine learningSample (material)Artificial intelligenceData miningEngineering
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Publication Info
- Year
- 1979
- Type
- article
- Volume
- 74
- Issue
- 365
- Pages
- 153-160
- Citations
- 917
- Access
- Closed
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Cite This
Seymour Geisser,
William F. Eddy
(1979).
A Predictive Approach to Model Selection.
Journal of the American Statistical Association
, 74
(365)
, 153-160.
https://doi.org/10.1080/01621459.1979.10481632
Identifiers
- DOI
- 10.1080/01621459.1979.10481632