Schneps, L;
Overill, R;
Lagnado, D;
(2018)
Ranking the Impact of Different Tests on a Hypothesis in a Bayesian Network.
Entropy
, 20
(11)
, Article 856. 10.3390/e20110856.
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Abstract
Testing of evidence in criminal cases can be limited by temporal or financial constraints or by the fact that certain tests may be mutually exclusive, so choosing the tests that will have maximal impact on the final result is essential. In this paper, we assume that a main hypothesis, evidence for it and possible tests for existence of this evidence are represented in the form of a Bayesian network, and use three different methods to measure the impact of a test on the main hypothesis. We illustrate the methods by applying them to an actual digital crime case provided by the Hong Kong police. We conclude that the Kullback-Leibler divergence is the optimal method for selecting the tests with the highest impact.
| Type: | Article |
|---|---|
| Title: | Ranking the Impact of Different Tests on a Hypothesis in a Bayesian Network |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.3390/e20110856 |
| Publisher version: | https://doi.org/10.3390/e20110856 |
| Language: | English |
| Additional information: | Copyright © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Bayesian networks; impact measures; Kullback–Leibler divergence; tornado method |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10064443 |
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