A very simple example demonstrates that Fisher's application of the conditionality principle to regression ("fixed $x$ regression"), endorsed by Sprott and many other followers, makes prediction impossible in the context of statistical learning theory. On the other hand, relaxing the requirement of conditionality makes it possible via, e.g., conformal prediction.

翻译：一个非常简单的例子表明，Fisher 对条件性原理在回归分析中的应用（即"固定 $x$ 回归"）——该应用得到了 Sprott 及众多追随者的认可——使得统计学习理论框架下的预测变得不可能。另一方面，放宽条件性要求则使得预测成为可能，例如通过保形预测（conformal prediction）等方法实现。