Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

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Abstract
Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a three-way view decision model based on decision-theoretic rough set model is proposed, in which optimistic decision, pessimistic decision, and equable decision are provided according to the cost of misclassification. The thresholds of probabilistic inclusion are calculated based on minimization of risk cost under respective decision bias. The study not only presents a new theoretic decision model considering the different personality of the decision makers, but also provides a practical explanation and an illustrative example on diverse risk bias decision.

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