Abstract
In uncertain environment, this paper investigates the induction of decision trees based on D-S evidence theory. This framework allows us to handle the case where the test attributes and decision attribute of training instances are all represented by belief functions. A novel attribute selection measure is introduced. We also propose a new evidential combination rule to combine the classification results with different matching coefficients.
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Guo, H., Shi, W., Du, F. (2005). EDTs: Evidential Decision Trees. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_49
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DOI: https://doi.org/10.1007/11540007_49
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
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