ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming

Yunsong Guo; Bart Selman

doi:10.1109/ICTAI.2007.140

I
ICTAI
2007
19th IEEE International Conference on Tools with Artificial Intelligence - Vol.2 (ICTAI 2007)
Abstract - ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming

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19th IEEE International Conference on Tools with Artificial Intelligence - Vol.2 (ICTAI 2007)

ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming

Paris, France

October 29-October 31

ISBN: 0-7695-3015-X

	ASCII Text	x
	Yunsong Guo, Bart Selman, "ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming," 2012 IEEE 24th International Conference on Tools with Artificial Intelligence, vol. 2, pp. 226-22-, 19th IEEE International Conference on Tools with Artificial Intelligence - Vol.2 (ICTAI 2007), 2007.

	BibTex	x
	@article{ 10.1109/ICTAI.2007.140, author = {Yunsong Guo and Bart Selman}, title = {ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming}, journal ={2012 IEEE 24th International Conference on Tools with Artificial Intelligence}, volume = {2}, year = {2007}, issn = {1082-3409}, pages = {226-22-}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICTAI.2007.140}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - 2012 IEEE 24th International Conference on Tools with Artificial Intelligence TI - ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming SN - 1082-3409 SP226 EP22- A1 - Yunsong Guo, A1 - Bart Selman, PY - 2007 VL - 2 JA - 2012 IEEE 24th International Conference on Tools with Artificial Intelligence ER -

Yunsong Guo

Bart Selman

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICTAI.2007.140

In this paper we developed an Inductive Logic Pro- gramming (ILP) based framework ExOpaque that is able to extract a set of Horn clauses from an arbitrary opaque machine learning model, to describe the behavior of the opaque model with high fidelity while maintaining the sim- plicity of the Horn clauses for human interpretations.

Citation:

Yunsong Guo, Bart Selman, "ExOpaque: A Framework to Explain Opaque Machine Learning Models Using Inductive Logic Programming," ictai, vol. 2, pp.226-22-, 19th IEEE International Conference on Tools with Artificial Intelligence - Vol.2 (ICTAI 2007), 2007

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