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Varieties of Justification in Machine Learning

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons83866

Corfield,  D
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Corfield, D. (2010). Varieties of Justification in Machine Learning. Minds and Machines, 20(2), 291-301. doi:10.1007/s11023-010-9191-1.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-BF36-1
Abstract
Forms of justification for inductive machine learning techniques are discussed and classified into four types. This is done with a view to introduce some of these techniques and their justificatory guarantees to the attention of philosophers, and to initiate a discussion as to whether they must be treated separately or rather can be viewed consistently from within a single framework.