基于证据的比较模型选择:一个理论的草图
Prasanta S Bandyopadhyay1, Samidha Shetty2, Gordon Brittan1
1Department of History and Philosophy, Montana State University, Bozeman, MT 59717, USA.
Entropy (Basel, Switzerland)
|January 28, 2026
概括
本研究介绍了一种非主观的基于证据的比较模型选择 (CEMC) 框架,用于认识的实用性. CEMC评估基于数据支持和相对距离的模型,整合预测和解释目标.
科学领域:
- 决策理论 决策理论
- 认识论的认识论学.
- 统计推理 统计推理
背景情况:
- 现有的决策理论文学被主观贝叶斯式和尼曼-皮尔森 (NP) 方法所主导.
- 证据决策理论虽然是最新的,但往往保留了主观主义贝叶斯式的导向.
- 需要一个非主观的模型选择框架.
研究的目的:
- 推进一个非主观的,基于证据的模型选择 (CEMC) 认识实用性的解释.
- 将预测和解释的认识目标整合到一个统一的框架内.
- 在CEMC框架内确定适当的统计工具来衡量认识效用.
主要方法:
- 阐明一个框架,以非主观的,比较的,基于证据的模型选择,以认识的实用性为基础.
- 在这个框架内,确定统计工具来衡量认识的实用性.
- 将CEMC与非比较的证据依据决策理论方法进行对比.
主要成果:
- 开发了一个新的CEMC框架,用于显式非主观的认识实用性.
- 通过评估基于数据支持和相对距离的模型,展示了CEMC如何整合预测和解释.
- 与非比较方法 (如基于区间的概率) 区别的CEMC.
结论:
- CEMC为推理提供了一个哲学框架,它统一了预测和解释.
- 该框架为现有的决策理论方法提供了一个非主观的替代方案.
- 模型选择标准与CEMC的核心承诺密切相关.
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