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.
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The author thanks the Max Planck Society for supporting his research for this paper.
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Corfield, D. Varieties of Justification in Machine Learning. Minds & Machines 20, 291–301 (2010). https://doi.org/10.1007/s11023-010-9191-1
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DOI: https://doi.org/10.1007/s11023-010-9191-1