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基于加权Bayes分类算法的不完备信息系统数据挖掘研究
引用本文:李莉,赵晋强.基于加权Bayes分类算法的不完备信息系统数据挖掘研究[J].数字社区&智能家居,2007(17).
作者姓名:李莉  赵晋强
作者单位:中国防卫科技学院文理学院,信息工程系,北京,101604 总参谋部陆航研究所,北京,101114
摘    要:基于相似粗集理论模型,对加权朴素Bayes算法进行了扩展,同时改进了传统不完备信息系统中缺失信息的弥补方法,并由此提出了基于不完备信息系统的加权Bayes分类算法,阐述了其对于不完备系统数据挖掘的重要意义,通过计算机仿真实验验证了该方法的有效性.

关 键 词:粗集理论  加权朴素Baves  不完备信息系统  数据挖掘

Reseach for Data Mining of Incomplete Information Systems Based on Weighted Naive Classification Algorithm
LI Li,ZHAO Jin-qiang.Reseach for Data Mining of Incomplete Information Systems Based on Weighted Naive Classification Algorithm[J].Digital Community & Smart Home,2007(17).
Authors:LI Li  ZHAO Jin-qiang
Affiliation:LI Li1,ZHAO Jin-qiang2
Abstract:Weighted Na?ve Classification Algorithm is extended based on Comparability Rough sets theory.The original recuperation method of lost information in Incomplete Information Systems is improved too.Weighted Na?ve Classification Algorithm based on Incomplete Information Systems is developed,and its significance for data mining is also set forth.Simulation results on a variety of data set illustrate the efficiency of this new algorithm.
Keywords:Rough set theory  Weighted Na?ve bayes  Incomplete Information System  Data mining
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