arXiv
Open Access
2024
Internalist Reliabilism in Statistics and Machine Learning: Thoughts on Jun Otsuka's Thinking about Statistics
Hanti Lin
Abstrak
Otsuka (2023) argues for a correspondence between data science and traditional epistemology: Bayesian statistics is internalist; classical (frequentist) statistics is externalist, owing to its reliabilist nature; model selection is pragmatist; and machine learning is a version of virtue epistemology. Where he sees diversity, I see an opportunity for unity. In this article, I argue that classical statistics, model selection, and machine learning share a foundation that is reliabilist in an unconventional sense that aligns with internalism. Hence a unification under internalist reliabilism.
Topik & Kata Kunci
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Hanti Lin
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Informasi Jurnal
- Tahun Terbit
- 2024
- Bahasa
- en
- Sumber Database
- arXiv
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- Open Access ✓