Abstract
In this paper, we propose a new rough set classifier induced from partially uncertain decision system. The proposed classifier aims at simplifying the uncertain decision system and generating more significant belief decision rules for classification process. The uncertainty is reperesented by the belief functions and exists only in the decision attribute and not in condition attribute values.
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© 2009 Springer-Verlag Berlin Heidelberg
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Trabelsi, S., Elouedi, Z., Lingras, P. (2009). Belief Rough Set Classifier. In: Gao, Y., Japkowicz, N. (eds) Advances in Artificial Intelligence. Canadian AI 2009. Lecture Notes in Computer Science(), vol 5549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01818-3_37
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DOI: https://doi.org/10.1007/978-3-642-01818-3_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01817-6
Online ISBN: 978-3-642-01818-3
eBook Packages: Computer ScienceComputer Science (R0)