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Multitype Pattern Discovery Via AQ21: A Brief Description of the Method and Its Novel Features

Show simple item record Wojtusiak, Janusz Michalski, Ryszard S. Kaufman, Kenneth A. Pietrzykowski, Jaroslaw 2006-11-03T18:17:34Z 2006-11-03T18:17:34Z 2006-06 en_US
dc.identifier.citation Wojtusiak, J., Michalski, R. S., Kaufman, K. and Pietrzykowski, J., "Multitype Pattern Discovery Via AQ21: A Brief Description of the Method and Its Novel Features," Reports of the Machine Learning and Inference Laboratory, MLI 06-2, George Mason University, Fairfax, VA, June, 2006. en_US
dc.description.abstract The AQ21 program seeks different types of patterns in data and represents them in human-oriented forms resembling natural language descriptions. Because of the latter feature it is called a natural induction program. This feature is achieved by employing a highly expressive representation language, Attributional Calculus, that combines aspects of propositional, predicate and multi-valued logic for the purpose of supporting pattern discovery and inductive learning. This paper briefly describes the pattern discovery mode in AQ21, and several novel abilities seamlessly integrated in it, specifically, to discover different types of attributional patterns depending on the parameter settings, to optimize patterns according to a large number of different pattern quality criteria, to learn rules with exceptions, to determine optimized sets of alternative hypotheses generalizing the same data, and to handle data with missing, irrelevant and/or not-applicable meta-values. The discovered patterns are expressed in the form of attributional rules that are directly interpretable in natural language and are visualized using either general logic diagrams or concept association graphs. The described program features are illustrated by a sample of pattern discovery problems.
dc.description.sponsorship This research has been conducted in the Machine Learning and Inference Laboratory of George Mason University, whose research activities have been supported in part by the National Science Foundation Grants No. IIS 9906858 and IIS 0097476, and in part by the UMBC/LUCITE #32 grant. en_US
dc.format.extent 3308 bytes
dc.format.extent 169616 bytes
dc.format.mimetype text/xml
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.relation.ispartofseries P 06-2 en_US
dc.relation.ispartofseries MLI 06-2 en_US
dc.subject pattern discovery en_US
dc.subject data mining en_US
dc.subject Machine learning en_US
dc.subject AQ learning en_US
dc.subject meta-values en_US
dc.subject knowledge visualization en_US
dc.title Multitype Pattern Discovery Via AQ21: A Brief Description of the Method and Its Novel Features en_US
dc.type Technical report en_US

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