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Reasoning with Meta-values in AQ Learning

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dc.contributor.author Michalski, Ryszard S.
dc.contributor.author Wojtusiak, Janusz
dc.date.accessioned 2006-11-03T18:17:30Z
dc.date.available 2006-11-03T18:17:30Z
dc.date.issued 2005-06 en_US
dc.identifier.citation Michalski, R. S. and Wojtusiak, J., "Reasoning with Meta-values in AQ Learning," Reports of the Machine Learning and Inference Laboratory, MLI 05-1, George Mason University, Fairfax, VA, June, 2005. en_US
dc.identifier.uri https://hdl.handle.net/1920/1491
dc.description.abstract This paper describes methods for reasoning with missing, irrelevant and not applicable meta-values in the AQ attributional rule learning. The methods address issues of handling these values in datasets both for rule learning and rule testing. In rule learning, the presence of these values affects the extension-against generalization operator in star generation, and the rule matching operator. In rule testing, these values affect the execution of the rule matching operator. The presented methods have been implemented in the AQ21 learning program and tested on four datasets.
dc.format.extent 1809 bytes
dc.format.extent 162040 bytes
dc.format.mimetype text/xml
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.relation.ispartofseries P 05-2 en_US
dc.relation.ispartofseries MLI 05-1 en_US
dc.subject Machine learning en_US
dc.subject concept learning en_US
dc.subject AQ learning en_US
dc.subject meta-values en_US
dc.title Reasoning with Meta-values in AQ Learning en_US
dc.type Technical report en_US


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