Model selection in science: The problem of language variance

British Journal for the Philosophy of Science 50 (1):83-102 (1999)
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Abstract

Recent solutions to the curve-fitting problem, described in Forster and Sober ([1995]), trade off the simplicity and fit of hypotheses by defining simplicity as the paucity of adjustable parameters. Scott De Vito ([1997]) charges that these solutions are 'conventional' because he thinks that the number of adjustable parameters may change when the hypotheses are described differently. This he believes is exactly what is illustrated in Goodman's new riddle of induction, otherwise known as the grue problem. However, the 'number of adjustable parameters' is actually a loose way of referring to a quantity that is not language dependent. The quantity arises out of Akaike's theorem in a way that ensures its language invariance.

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Monte Forster
University of Calgary

Citations of this work

Prediction versus accommodation and the risk of overfitting.Christopher Hitchcock & Elliott Sober - 2004 - British Journal for the Philosophy of Science 55 (1):1-34.
Bayes Not Bust! Why Simplicity Is No Problem for Bayesians.David L. Dowe, Steve Gardner & and Graham Oppy - 2007 - British Journal for the Philosophy of Science 58 (4):709 - 754.
A Categorical Solution to the Grue Paradox.Tatsuya Yoshii & Jun Otsuka - forthcoming - British Journal for the Philosophy of Science.

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References found in this work

The accuracy of predictions.David Miller - 1975 - Synthese 30 (1-2):159 - 191.
Forster and Sober on the curve-fitting problem.André Kukla - 1995 - British Journal for the Philosophy of Science 46 (2):248-252.

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