Prediction versus accommodation and the risk of overfitting

Abstract
an observation to formulate a theory, it is no surprise that the resulting theory accurately captures that observation. However, when the theory makes a novel prediction—when it predicts an observation that was not used in its formulation—this seems to provide more substantial confirmation of the theory. This paper presents a new approach to the vexed problem of understanding the epistemic difference between prediction and accommodation. In fact, there are several problems that need to be disentangled; in all of them, the key is the concept of overfitting. We float the hypothesis that accommodation is a defective methodology only when the methods used to accommodate the data fail to guard against the risk of overfitting. We connect our analysis with the proposals that other philosophers have made. We also discuss its bearing on the conflict between instrumentalism and scientific realism. Introduction Predictivisms—a taxonomy Observations Formulating the problem What might Annie be doing wrong? Solutions Observations explained Mayo on severe tests The miracle argument and scientific realism Concluding comments.
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DOI 10.1093/bjps/55.1.1
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K. Steele & C. Werndl (2013). Climate Models, Calibration, and Confirmation. British Journal for the Philosophy of Science 64 (3):609-635.
Guillaume Rochefort-Maranda (2016). Simplicity and Model Selection. European Journal for Philosophy of Science 6 (2):261-279.
David Harker (2008). On the Predilections for Predictions. British Journal for the Philosophy of Science 59 (3):429-453.
Richard Dawid, Stephan Hartmann & Jan Sprenger (2015). The No Alternatives Argument. British Journal for the Philosophy of Science 66 (1):213-234.

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