基于收益和风险优化的属性约简算法

Attribute Reduction Algorithm on Balancing Profit and Risk

决策者总是希望实现收益最大而承担的风险最小,如何平衡或兼顾两者,可考虑引入收益和风险因素进行属性约简以便做出寻找有效的、切实可行的决策。在一定的预期收益水平下通过优化组合收益和风险,结合粗糙集和贝叶斯模型,建立了收益和风险优化的决策模型,以每个属性的收益风险平衡组合函数作为指标进行启发式属性约简,该算法减少数据模型的规模和复杂度,并提高模型系统的仿真精度。

Usually it is taken for granted to achieve the maximal profit at the cost of the minimal risk. It is an important problem of how to balance profit and risk, considering introducing profit and risk to attribute reduction so as to find practical algorithms in decision-making process. A decision-theoretic model was built, which could balance profit and risk combining with decision-theoretic rough set model and minimum risk of Bayes decision and find optimal combinations of risk in a certain level of expected profit, then a heuristic algorithm of attribute reduction was proposed, which took the function of balancing profit and risk as the target of heuristic attribute reduction, and it could reduce the scales and complexity of data model, and then improve the simulation precision of the model system.