关键词: 数据挖掘, 粗糙集, 属性约简, 强化属性依赖度, 粒度, 经济损失

Abstract:

As the core of rough set, the attribute reduction theory is difficult to make a reduction when there are too many secondary attributes. Based on the enhanced attribute dependability of rough set, a data mining model is constructed. In this model, the dependability of each attribute in group is calculated, and the dependability in combination is merged into each attribute to enhance the attribute dependability. For the rational of exploration model calculation process, a exploration model and a discretization method are built. The range of discrete quantity and attribute combination is narrowed. As the value of attributes, the obtained dependability is used to find the important attributes. The experimental results show that compared with the traditional attribute reduction, this model can more effectively analyze the importance of attributes and solve the difficult problem of reduction in the analysis of factors affecting the economic loss after the earthquake of magnitude 5 or above in some areas. The result of this model in test data is 86% consistent with that of the traditional method.

Key words: data mining, rough set, attribute reduction, dependability enhancement, granularity, economic loss