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Democratic three-way decisions based on voting mechanism
International Journal of Machine Learning and Cybernetics ( IF 5.6 ) Pub Date : 2021-07-17 , DOI: 10.1007/s13042-021-01367-9
Qinghua Zhang 1 , Xuechao Zhi 1 , Yongyang Dai 1 , Guoyin Wang 1
Affiliation  

In some cases, the decision process of three-way decisions (3WD) is costly, and sequential three-way decisions (S3WD) may cause errors beyond tolerance. To solve the above problems, in this paper, democratic three-way decisions based on voting mechanism (D3WD-VM) is proposed from the perspective of all conditional attributes. By obtaining decision opinions of different attributes at the coarse granularity level, the final decision results is obtained. First, a voting mechanism is established to realize the idea of the democratic three-way, which is an ensemble decision space based on conditional attributes. Next, in order to make the decision results more reasonable, the normalized information gain ratio is utilized to optimize the voting weight of conditional attributes in the voting mechanism. Then, based on cognitive science, two different decision strategies are devised to make the final decision. Finally, the experimental results demonstrate that the accuracy rate and the comprehensive evaluation index of the D3WD-VM have also been improved to some extent compared with the S3WD, and the decision efficiency is better than 3WD.



中文翻译:

基于投票机制的民主三通决策

在某些情况下,三向决策 (3WD) 的决策过程成本高昂,而顺序三向决策 (S3WD) 可能会导致超出容忍度的错误。针对上述问题,本文从所有条件属性的角度提出了基于投票机制的民主三路决策(D3WD-VM)。通过在粗粒度级别获取不同属性的决策意见,得到最终的决策结果。首先,建立投票机制,实现民主三路的思想,即基于条件属性的集合决策空间。接下来,为了使决策结果更加合理,在投票机制中利用归一化信息增益比来优化条件属性的投票权重。然后,基于认知科学,设计了两种不同的决策策略来做出最终决策。最后,实验结果表明,与S3WD相比,D3WD-VM的准确率和综合评价指标也有一定程度的提高,决策效率优于3WD。

更新日期:2021-07-18
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