【摘要】 提出了一种基于变精度粗糙集理论的规则挖掘算法 .通过粗糙规则集的不确定性量度 ,应用遗传算法求取相对属性约简 ,然后根据所给阈值导出粗糙规则集 ,并对阈值对规则集的影响进行了事后分析 .由该算法得到的规则既有一定的噪声容忍度又具备较高的准确度和覆盖度 ,从而能充分保证预测和分类的准确性 .实例分析证明 ,该算法是规则挖掘的有效方法 .更多还原

【Abstract】 A rough rules mining approach based on variable precision rough set theory is proposed in this paper. With uncertain measurement of rough rules set, relative attribute reduction is obtained by applying GA, and then rough rules set is deduced under the threshold values. The effect of threshold values on the rules set is discussed in this paper. The rules obtained by this approach have a certain noise tolerance, more precision and better overlay. So the accuracy of forecasting and classifying are assured. The practical results show that the approach is effective in solving knowledge mining problems.更多还原