Abstract
We investigate association reducts, which extend previously studied information and decision reducts in capability of expressing dependencies between groups of attributes in data. We formulate optimization problems related to the most informative associations between groups of attributes. We provide heuristic mechanisms for addressing those problems. We also discuss at more general level how to express approximate dependencies between groups of attributes.
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Ślęzak, D. (2006). Association Reducts: Complexity and Heuristics. In: Greco, S., et al. Rough Sets and Current Trends in Computing. RSCTC 2006. Lecture Notes in Computer Science(), vol 4259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11908029_18
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DOI: https://doi.org/10.1007/11908029_18
Publisher Name: Springer, Berlin, Heidelberg
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