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On reducing information systems by accuracy measures in rough sets

机译:通过粗糙集中的准确度降低信息系统

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In this paper, we discuss on reducing information systems from some aspects. Assuming that some classes are more important than the other in medical diagnosis, all the classes are divided into two groups by considering importance grades of classes. In reducing attributes, the accuracy measures of the important group should not be reduced, while those of the other group can be slightly reduced. Furthermore, introducing an order relation with regard to importance grades, the given information system is reformed so that predictive rules from reformed one are permissive for patients in medical diagnosis.
机译:在本文中,我们从某些方面讨论减少信息系统。假设某些课程比其他医疗诊断更重要,所以通过考虑课程的重要性等级,所有课程分为两组。在减少属性中,不应减少重要组的准确度措施,而其他组的准确度可以略微减少。此外,引入关于重要性等级的订单关系,给定的信息系统进行了改革,使得来自改革的预测规则是医学诊断患者的允许。

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