Information-Corrected Estimation: A Generalization Error Reducing Parameter Estimation Method
Modern computational models in supervised machine learning are often highly parameterized universal approximators. As such, the value of the parameters is unimportant, and only the out of sample performance is considered. On the other hand much of the literature on model estimation assumes that the...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
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| Accès en ligne: | https://doaj.org/article/ab0ad735d21a46f785cc82159c6ac2f9 |
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