This article reveals one general scheme for creating counter examples to Bayesian confirmation theory. The reason of the problems is that: in daily life the degree of confirmation is affected not only by probability but also by some non-probabilistic factors, e.g., structural similarity, quantity of evidence, and marginal utility, while Bayesian confirmation theory considers only probabilities to measure the degree of confirmation. This article resolves these problems after some detail analyses, and proposes a new confirmation measure based on these factors.

中文翻译：

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贝叶斯确认还是普通确认？

本文揭示了一种创建贝叶斯确认理论反例的一般方案。问题的原因在于：在日常生活中，确认的程度不仅受概率的影响，还受到一些非概率因素的影响，如结构相似性、证据数量、边际效用等，而贝叶斯确认理论只考虑概率来衡量确认的程度。本文通过详细分析解决了这些问题，并基于这些因素提出了新的确认措施。