Varieties of Justification in Machine Learning

  • Authors:
  • David Corfield

  • Affiliations:
  • SECL, University of Kent, Canterbury, UK

  • Venue:
  • Minds and Machines
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

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.