Same-Decision Probability: threshold robustness and application to explanation
Publication date
2018-09
Authors
Renooij, Silja
Editors
Kratochvíl, Václav
Studený, Milan
Advisors
Supervisors
DOI
Document Type
Part of book
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Abstract
The same-decision probability (SDP) is a confidence measure for threshold-based decisions. In this paper we detail various properties of the SDP that allow for studying its robustness to changes in the threshold value upon which a decision is based. In addition to expressing confidence in a decision, the SDP has proven to be a useful tool in other contexts, such as that of information gathering. We demonstrate that the properties of the SDP as established in this paper allow for its application in the context of explaining Bayesian network classifiers as well.
Keywords
Bayesian network classifiers, threshold-based decisions, Same-decision probability, robustness, explanations
Citation
Renooij, S 2018, Same-Decision Probability: threshold robustness and application to explanation. in V Kratochvíl & M Studený (eds), Proceedings of the Ninth International Conference on Probabilistic Graphical Models (PGM). Proceedings of Machine Learning Research, vol. 72, pp. 368-379, Ninth International Conference on Probabilistic Graphical Models (PGM), Prague, Czech Republic, 11/09/18. < http://proceedings.mlr.press/v72/renooij18a/renooij18a.pdf >, conference