Abstract
This paper proposes a method to acquire rules for evidential reasoning from multiple decision tables. The knowledge acquisition consists of two steps: the first step derives uncertain rules of the form: if a(u) is x, then d(u) is in Y 1 with r 1 or . . . or d(u) is in Y M with r M , where r j (j = 1, . . . ,M) are beliefs represented by basic belief assignment. The second step derives rules of the form: if a(u) is in X, then d(u) is in Y 1 with r 1 or . . . or d(u) is in Y M with r M , from the rules obtained in the first step. A non-specificity based condition imposed on rules generated in the second step is introduced. It is also shown that the disjunctive combination approach satisfies the condition.
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Yamada, K., Kimala, V. (2010). Acquiring Knowledge from Decision Tables for Evidential Reasoning. In: Huynh, VN., Nakamori, Y., Lawry, J., Inuiguchi, M. (eds) Integrated Uncertainty Management and Applications. Advances in Intelligent and Soft Computing, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11960-6_38
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DOI: https://doi.org/10.1007/978-3-642-11960-6_38
Publisher Name: Springer, Berlin, Heidelberg
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