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Conditionality Principle Under Unconstrained Randomness
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DOI：10.1214/25-STS982.png)
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Abstract
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A very simple example demonstrates that Fisher's application of the conditionality principle to regression (fixed-x regression), endorsed by David 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, for example, conformal prediction.
Keywords:
Assumption of randomness
conditionality princi ple
machine learning
prediction
regression
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