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基于粒化单调的不完备混合型数据增量式属性约简算法
引用本文:张雨新,孙达明,李飞. 基于粒化单调的不完备混合型数据增量式属性约简算法[J]. 计算机应用与软件, 2021, 38(3): 279-286. DOI: 10.3969/j.issn.1000-386x.2021.03.042
作者姓名:张雨新  孙达明  李飞
作者单位:唐山工业职业技术学院信息工程系 河北 唐山 063299;唐山工业职业技术学院信息工程系 河北 唐山 063299;东北大学计算中心 河北 秦皇岛 066004
基金项目:河北省教育厅创新创业课题项目
摘    要:增量式属性约简是一种针对动态数据集的新型属性约简方法.然而目前的增量式属性约简很少有对不完备混合型的信息系统进行研究.针对这类问题提出一种属性增加时的增量式属性约简算法.在不完备混合型信息系统下引入邻域容差关系.基于邻域容差关系的粒化单调性,提出信息系统属性增加时邻域容差条件熵的增量式更新方法,并提出了不完备混合型信息...

关 键 词:粗糙集  粒计算  属性约简  动态数据集  增量式学习

INCREMENTAL ATTRIBUTE REDUCTION ALGORITHM FOR INCOMPLETE MIXED DATA BASED ON GRANULATION MONOTONY
Zhang Yuxin,Sun Daming,Li Fei. INCREMENTAL ATTRIBUTE REDUCTION ALGORITHM FOR INCOMPLETE MIXED DATA BASED ON GRANULATION MONOTONY[J]. Computer Applications and Software, 2021, 38(3): 279-286. DOI: 10.3969/j.issn.1000-386x.2021.03.042
Authors:Zhang Yuxin  Sun Daming  Li Fei
Affiliation:(Department of Information Engineering,Tangshan Polytechnic College,Tangshan 063299,Hebei,China;Computing Center,Northeastern University,Qinhuangdao 066004,Hebei,China)
Abstract:Incremental attribute reduction is a new formal attribute reduction method for dynamic data sets.However,there are few studies on incomplete hybrid information systems for incremental attribute reduction.To solve these problems,an incremental attribute reduction algorithm with increasing attributes is proposed.In this paper,the neighborhood tolerance relation was introduced in incomplete hybrid information system.Based on the granulation monotony of neighborhood tolerance relation,an incremental updating method of neighborhood tolerance condition entropy was proposed when the attribute of information system was increased,and an incremental attribute reduction algorithm based on neighborhood tolerance condition entropy was proposed for incomplete hybrid information systems.The experimental results show the effectiveness of the proposed algorithm.
Keywords:Rough set  Granular computing  Attribute reduction  Dynamic data set  Incremental learning
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