Imperial College London
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ProfessorFrancescaToni

Faculty of Engineering, Department of Computing

Professor in Computational Logic
 
 
 
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Contact

 

+44 (0)20 7594 8228f.toni Website

 
 
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Location

 

430Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Albini:2021:10.1007/978-3-030-89188-6_7,
author = {Albini, E and Rago, A and Baroni, P and Toni, F},
doi = {10.1007/978-3-030-89188-6_7},
pages = {88--100},
publisher = {Springer Verlag},
title = {Influence-driven explanations for bayesian network classifiers},
url = {http://dx.doi.org/10.1007/978-3-030-89188-6_7},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - We propose a novel approach to buildinginfluence-driven ex-planations(IDXs) for (discrete) Bayesian network classifiers (BCs). IDXsfeature two main advantages wrt other commonly adopted explanationmethods. First, IDXs may be generated using the (causal) influences between intermediate,  in  addition  to  merely  input  and  output,  variables within  BCs, thus providing adeep, rather than shallow, account of theBCs’ behaviour. Second, IDXs are generated according to a configurable set of properties, specifying which influences between variables count to-wards  explanations.  Our  approach  is  thusflexible and  can  be  tailored to the requirements of particular contexts or users. Leveraging on this flexibility, we propose novel IDX instances as well as IDX instances cap-turing existing approaches. We demonstrate IDXs’ capability to explainvarious  forms  of  BCs,  and  assess  the  advantages  of  our  proposed  IDX instances with both theoretical and empirical analyses.
AU  - Albini,E
AU  - Rago,A
AU  - Baroni,P
AU  - Toni,F
DO  - 10.1007/978-3-030-89188-6_7
EP  - 100
PB  - Springer Verlag
PY  - 2021///
SN  - 0302-9743
SP  - 88
TI  - Influence-driven explanations for bayesian network classifiers
UR  - http://dx.doi.org/10.1007/978-3-030-89188-6_7
UR  - https://link.springer.com/chapter/10.1007/978-3-030-89188-6_7
UR  - http://hdl.handle.net/10044/1/92100
ER  -
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