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基于遗传算法的粗糙集混合数据属性约简

Rough set reduction for hybrid data based on genetic algorithm

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【作者】 叶玉玲伞冶

【Author】 YE Yu-ling,SAN Ye(Control and Simulation Center,Harbin Institute of Technology,Harbin 150080,China)

【机构】 哈尔滨工业大学控制与仿真中心哈尔滨工业大学控制与仿真中心 哈尔滨150080哈尔滨150080

【摘要】 为了对现实中既含有离散数据又有连续数据,甚至还有模糊数据的决策系统进行属性约简,基于模糊等价关系建立粗糙集模型,用熵来度量粗糙集中的不可分辨能量并定义约简.提出用遗传算法来求解含混合数据的决策系统的约简,论述了适应度函数的选择,给出了算法的具体实现.对经典数据集和UC I机器学习数据库中5个数据库约简的结果证明了算法的有效性和可行性.

【Abstract】 In order to reduce the real decision systems coming with discrete data as well as continuous data,even fuzzy data,a new rough set theory model based on fuzzy equation relation was established.Entropy was presented to measure the indiscernibility power and define the reduction.The genetic algorithm was proposed to reduce decision systems made up of hybrid data,the fitness function and reduction algorithm were presented as well.The validity and feasibility of the algorithm were demonstrated by the results of experiments on a classical data set and five UCI machine learning databases.

【基金】 国家自然科学基金资助项目(60474069)
  • 【文献出处】 哈尔滨工业大学学报 ,Journal of Harbin Institute of Technology , 编辑部邮箱 ,2008年05期
  • 【分类号】TP18
  • 【被引频次】26
  • 【下载频次】367
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