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中文摘要：
针对可能存在分类误差缺失信息的群体分类决策问题，提出了一种可以从多个决策表中获取群体分类偏好的可变精度粗糙集方法。该方法通过控制决策者的分类误差率，群体分类一致率及反对率，将多个决策表中符合条件的信息汇集，形成群体分类模式表，然后根据每种分类模式在不同分类误差率和群体一致率下得到支持和反对的频数，得到群体分类模式集合的下近似，即群体分类偏好。给出了应用该方法的具体步骤，算例验证了该方法的有效性。
英文摘要：
For a kind of group decision classification problem with admissible classification error, a method aggregating group preference from multiple decision tables based on variable precision rough set is proposed. By controlling the admissible level of classification error in each table, the ratio of supporting and opposing decision tables to all decision tables, multiple tables are transformed into a group classification pattern table which includes summary information of all decision tables. And then group＇s classification preference is attained by analyzing the frequence of each pattern supported by decision makers in different classification error level and group agreement ratio. The solution procedure is given and the efficiency of this method is also showed by an example.
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