基于属性相容度和重要度的粗糙集

针对粗糙集属性约简算法中时间效率较低的问题,结合属性相容度模型和属性重要度的模型,提出一种混合相容度和重要度的粗糙集属性约简算法.该算法利用属性的相容度模型,快速地从众多属性中将核集筛选出来,作为基本核集；然后通过属性的重要度模型对基本核集进行补充和完善,作为约简后的最终核集,以确保核集的完整性.实验结果表明,在保证约简结果完整性的基础上,该混合模型算法,大大提高了时间效率,降低了算法的时间复杂度.

Attribute Reduction Algorithm of Rough Set Based on the Combined Compatibility and Importance of Attributes

According to rough set attribute reduction algorithm for the problem of low efficiency, combining the attribute compatibility model and the attribute importance model, the paper puts forward a kind of rough set attribute reduction algorithm based on the combined compatibility and importance. The algorithm using the compatibility model to quickly sift the core set from attributes as the basic core set, basic core set, regard as final core set ,was completed and improved by attribute importance model, the insurance of basic core set. The experimental results show that the algorithm improves the efficiency of the time, greatly reduces the time complexity of the algorithm.