基于邻域关系的知识粒度增量式属性约简算法

陈曦; 刘晶

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基于邻域关系的知识粒度增量式属性约简算法

更新时间：2026-09-04

- 基于邻域关系的知识粒度增量式属性约简算法
- Knowledge granularity incremental attribute reduction algorithm based on neighborhood relation
- 微电子学与计算机 2020年37卷第10期页码：1-6
- 作者机构：
  
  1. 华中科技大学管理学院,湖北,武汉,430074
  2. 武汉铁路职业技术学院机构,湖北,武汉,430200
- 作者简介：
- 基金信息：
  
  国家自然科学基金 71277097
- DOI：
  中图分类号：
- 纸质出版：2020
- 稿件说明：
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陈曦, 刘晶. 基于邻域关系的知识粒度增量式属性约简算法[J]. 微电子学与计算机, 2020, 37(10): 1-6.

CHEN Xi, LIU Jing. Knowledge granularity incremental attribute reduction algorithm based on neighborhood relation[J]. 2020, 37(10): 1-6.
陈曦, 刘晶. 基于邻域关系的知识粒度增量式属性约简算法[J]. 微电子学与计算机, 2020, 37(10): 1-6. DOI：

CHEN Xi, LIU Jing. Knowledge granularity incremental attribute reduction algorithm based on neighborhood relation[J]. 2020, 37(10): 1-6. DOI：

摘要

为了在邻域型信息系统下进行增量式属性约简的研究，采用邻域知识粒度构造出一种邻域型信息系统的增量式属性约简算法.首先将信息系统的知识粒度在邻域型信息系统下进行推广，提出了邻域知识粒度；然后针对属性增加的情形，研究了邻域知识粒度的增量式更新机制；最后基于这种机制设计出了相应的增量式属性约简算法.实验分析表明所提出的增量式算法具有较高的动态属性约简性能.

Abstract

In order to study incremental attribute reduction in neighborhood information system

an incremental attribute reduction algorithm of neighborhood information system is constructed by using neighborhood knowledge granularity. Firstly

the knowledge granularity of information system is extended in the neighborhood information system

and the neighborhood knowledge granularity is proposed. Secondly

the incremental updating mechanism of neighborhood knowledge granularity is studied for the case of attribute increase. Finally

the corresponding incremental attribute reduction algorithm is designed based on this mechanism. Experimental results show that the incremental algorithm has high dynamic attribute reduction performance.

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references

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