计算机应用与软件Issue(5)：264-267,294,5.DOI:10.3969/j.issn.1000-386x.2014.05.067
一种对象完备度优先填补的决策树规则提取算法
A DECISION TREE RULES EXTRACTION ALGORITHM WITH IMPUTATION PRIORITY IN OBJECT COMPLETENESS
摘要
Abstract
Decision rules extraction in incomplete information systems is an important issue to be studied in data mining field.We analyse the principal decision rules acquisition method in incomplete information system,and take the incomplete decision table with missing decision attribution values as the research object,propose a data imputation prior-based decision tree rules extraction algorithm.For the deficiency of ROUSTIDA algorithm that it has large amount of computation in data imputation and is easy to cause decision rule conflict,the algorithm adoptsthe idea of giving the imputation priority to decision attributes and introduces the concept of object completeness to improve it,and uses the improved ROUSTIDA algorithm for one-off preprocessing of data imputation on incomplete decision table,as well as employs attribute significancewhen in limited tolerance relation as the heuristic function to construct decision tree,so as to obtain the decision rule.Examples show that the method is effective,the generated decision rule is simple and has a higher accuracy.关键词
不完备信息系统/对象完备度/规则提取/决策树/数据填补Key words
Incomplete information systems/Object completeness/Rules extraction/Decision tree/Data imputation分类
信息技术与安全科学引用本文复制引用
陈家俊,苏守宝,金萍..一种对象完备度优先填补的决策树规则提取算法[J].计算机应用与软件,2014,(5):264-267,294,5.基金项目
国家自然科学基金项目（61075049，61375605）；安徽省高校自然科学研究重点项目（KJ2012A274）。 （）
