Abstract
We continue our research on decision bireducts. For a decision system \(\mathbb{A}\) = (U,A ∪ {d}), a decision bireduct is a pair (B,X), where B ⊆ A is a subset of attributes discerning all pairs of objects in X ⊆ U with different values on the decision attribute d, and where B and X cannot be, respectively, reduced and extended. We report some new results related to NP-hardness of extraction of optimal decision bireducts, heuristics aimed at searching for sub-optimal decision bireducts, and applications of decision bireducts to stream data mining.
This research was partly supported by the Polish National Science Centre (NCN) grants 2011/01/B/ST6/03867 and 2012/05/B/ST6/03215.
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Stawicki, S., Ślęzak, D. (2013). Recent Advances in Decision Bireducts: Complexity, Heuristics and Streams. In: Lingras, P., Wolski, M., Cornelis, C., Mitra, S., Wasilewski, P. (eds) Rough Sets and Knowledge Technology. RSKT 2013. Lecture Notes in Computer Science(), vol 8171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41299-8_19
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