Corfield, David (2010) Varieties of Justification in Machine Learning. Minds and Machines, 20 (2). pp. 291-301. ISSN 0924-6495. (doi:10.1007/s11023-010-9191-1) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:27989)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://dx.doi.org/10.1007/s11023-010-9191-1 |
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.
| Item Type: | Article |
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| DOI/Identification number: | 10.1007/s11023-010-9191-1 |
| Subjects: | B Philosophy. Psychology. Religion > B Philosophy (General) |
| Divisions: | Divisions > Division of Arts and Humanities > School of Culture and Languages |
| Depositing User: | David Corfield |
| Date Deposited: | 27 Jun 2011 14:13 UTC |
| Last Modified: | 05 Nov 2024 10:09 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/27989 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Corfield, David.
| Creator's ORCID: |
 https://orcid.org/0000-0003-0432-3221
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