Why and how to construct an epistemic justification of machine learning?
Consider a set of shuffled observations drawn from a fixed probability distribution over some instance domain. What enables learning of inductive generalizations which proceed from such a set of observations? The scenario is worthwhile because it epistemically characterizes most of machine learning....
| Publicado en: | Synthese Vol. 204; no. 2; pp. 1 - 25 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Aug2024
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| Acceso en línea: | Ver este registro en EBSCOhost |