Abstract
In the research of knowledge acquisition based on rough sets theory, attribute reduction is a key problem. Many researchers proposed some algorithms for attribute reduction. Unfortunately, most of them are designed for static data processing. However, many real data are generated dynamically. In this paper, an incremental attribute reduction algorithm is proposed. When new objects are added into a decision information system, a new attribute reduction can be got by this method quickly.
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Hu, F., Wang, G., Huang, H., Wu, Y. (2005). Incremental Attribute Reduction Based on Elementary Sets. In: Ślęzak, D., Wang, G., Szczuka, M., Düntsch, I., Yao, Y. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548669_20
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DOI: https://doi.org/10.1007/11548669_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28653-0
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