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Varieties of Justification in Machine Learning




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.

Author(s): Corfield, D.
Journal: Minds and Machines
Volume: 20
Number (issue): 2
Pages: 291-301
Year: 2010
Month: July
Day: 0

Department(s): Empirical Inference
Bibtex Type: Article (article)

Digital: 0
DOI: 10.1007/s11023-010-9191-1
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF


  title = {Varieties of Justification in Machine Learning},
  author = {Corfield, D.},
  journal = {Minds and Machines},
  volume = {20},
  number = {2},
  pages = {291-301},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = jul,
  year = {2010},
  month_numeric = {7}