Privacy and explainability: the effects of data protection on shapley values

HIGHLIGHTS

  • who: Aso Bozorgpanah and colleagues from the Department of Computing Science, Umeu00e5 University, Umeu00e5, Sweden Kerman, Kerman, Iran have published the article: Privacy and Explainability: The Effects of Data Protection on Shapley Values, in the Journal: Technologies 2022, 10, 125. of /2022/
  • what: The authors show that some degree of protection still permits to maintain the information of for the four machine learning models studied. The authors focus on explaining individual prediction. The aim of this paper is to better understand how masking methods affect explanations when these explanations are based on Shapley values. The . . .

     

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