杨新锋, 杨东芳, 刘克成, 辛玉林. 扩展的多类别信息熵的粗糙集连续属性离散化新方法[J]. 红外与激光工程, 2014, 43(11): 3802-3806.
引用本文: 杨新锋, 杨东芳, 刘克成, 辛玉林. 扩展的多类别信息熵的粗糙集连续属性离散化新方法[J]. 红外与激光工程, 2014, 43(11): 3802-3806.
Yang Xinfeng, Yang Dongfang, Liu Kecheng, Xin Yulin. Discretization of continuous attributes in rough set theory based on expanded multi-category information entropy[J]. Infrared and Laser Engineering, 2014, 43(11): 3802-3806.
Citation: Yang Xinfeng, Yang Dongfang, Liu Kecheng, Xin Yulin. Discretization of continuous attributes in rough set theory based on expanded multi-category information entropy[J]. Infrared and Laser Engineering, 2014, 43(11): 3802-3806.

扩展的多类别信息熵的粗糙集连续属性离散化新方法

Discretization of continuous attributes in rough set theory based on expanded multi-category information entropy

  • 摘要: 提出了一种标准粗糙集约简时连续属性离散化的新方法.采用标准粗糙集进行属性约简时,要求属性为离散的,而大多数情况下属性是连续的,因此需要进行离散化处理.首先介绍了原有的信息熵算法并指出其局限性;其次,对多类别信息熵进行扩充,将距离因素引入到该信息熵的计算中;最后给出了扩展信息熵计算的两个基本准则,利用证据理论完成信度的上聚焦.仿真显示了该方法的有效性.

     

    Abstract: A new discretized approach for continuous attributes was presented. As we know, the basic rough set theory can not deal with continuous attributes, so the continuous attributes need to be discretization. Firstly, the disadvantages of original information entropy were analyzed. Secondly, the distance factor was introduced to expand the information entropy. At last two basic rules were presented to calculate expanded information entropy and DS evidential theory was used to process the mass up-focus. Simulation results show the availability of this new information fusion algorithm.

     

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