Abstract
Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, out-dated sources and sampling errors. As a result there is a need for tools and techniques for mining and managing uncertain data. In this paper proposes a Rough Set method for handling data uncertainty. Rough set is a mathematical theory for dealing with uncertainty. Uncertainty implies inconsistencies, which are taken into account, so that the produced are categorized into certain and possible with the help of rough set theory Experimental results show that proposed model exhibits reasonable accuracy performance in classification on uncertain data.
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Suresh, G.V., Venkateswara Reddy, E., Srinivasa Reddy, E. (2012). Uncertain Data Classification Using Rough Set Theory. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds) Proceedings of the International Conference on Information Systems Design and Intelligent Applications 2012 (INDIA 2012) held in Visakhapatnam, India, January 2012. Advances in Intelligent and Soft Computing, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27443-5_100
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DOI: https://doi.org/10.1007/978-3-642-27443-5_100
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