Against Interpretability: a Critical Examination of the Interpretability Problem in Machine Learning
Crossref DOI link: https://doi.org/10.1007/s13347-019-00372-9
Published Online: 2019-08-13
Published Print: 2020-09
Update policy: https://doi.org/10.1007/springer_crossmark_policy
Krishnan, Maya http://orcid.org/0000-0002-8902-5241
Funding for this research was provided by:
All Souls College, University of Oxford (-)
Text and Data Mining valid from 2019-08-13
Version of Record valid from 2019-08-13
Article History
Received: 1 January 2019
Accepted: 31 July 2019
First Online: 13 August 2019