Generating Private Contrastive Explanations with Differentially Private Classifiers and Foil Trees

Master thesis (2021)

Authors

W.J. Zirkzee Electrical Engineering, Mathematics and Computer Science

Contributors

Mark A. Neerincx Interactive Intelligence (mentor)
S. Picek Cyber Security (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2021 Wouter Zirkzee
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Published Date

29-04-2021

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Due to the rapid growth of diseases like diabetes, machine-learning (ML) advanced clinical decision support systems (CDSS) that support doctors or patients in their care might prove to be a valuable asset. In the battle to make healthcare more accessible, adopting ML techniques could be supportive in increasing the overall
effectiveness and efficiency of healthcare. However, the development of a CDSS is troubled by multiple problems.

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