Learning Patterns in Noisy Data: The AQ Approach

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dc.contributor.authorMichalski, Ryszard S.
dc.contributor.authorKaufman, Kenneth A.
dc.date.accessioned2006-11-03T18:17:15Z
dc.date.available2006-11-03T18:17:15Z
dc.date.issued2001
dc.description.sponsorshipThis research was conducted in the Machine Learning and Inference Laboratory at George Mason University. The Laboratory's research activities have been supported in part by the National Science Foundation under Grants No. IIS-9906858 and IIS-9904078, and in part by the Grant No. UMBCV/MPO/LUCITE#32.
dc.format.extent1193 bytes
dc.format.extent125950 bytes
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dc.format.mimetypeapplication/pdf
dc.identifier.citationMichalski, R. S. and Kaufman, K., "Learning Patterns in Noisy Data: The AQ Approach," Machine Learning and its Applications, G. Paliouras, V. Karkaletsis and C. Spyropoulos (Eds.), pp. 22-38, Springer-Verlag, 2001.
dc.identifier.urihttps://hdl.handle.net/1920/1476
dc.language.isoen_US
dc.relation.ispartofseriesP 01-6
dc.titleLearning Patterns in Noisy Data: The AQ Approach
dc.typePreprint

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