| 摘要: |
| 本文利用粗糙集理论中条件属性相对于决策属性的核，解决多变量检验中属性的选择问题．另外，定义了２个等价关系相对泛化的概念，并将它用于解决多变量检验的构造问题．通过一个例子，对本文提出的多变量决策树方法与著名的单变量决策树（ＩＤ３）方法进行了比较，结果表明前者比后者更简单．同时，对几种多变量决策树方法做了初步的对比分析． |
| 关键词: 粗糙集 单变量决策树 多变量决策树 归纳学习 属性的相对核 |
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| 基金项目:本文研究得到国家863高科技项目资助. |
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| MODELING TEMPORAL SEMANTICS INFORMATION FOR NATURAL LANGUAGE |
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GUO Honglei,YAO Tianshun
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| Abstract: |
| In this paper，the core of condition attributes with respect to decision attributes in rough sets theory is used for selection of attributes in multivariate tests．A new concept of generalization of one equivalence relation with respect to another one is introduced and used for construction of multivariate tests．The comparison between multi-variate decision tree and univariate decision tree is done through an example．The results show that the former is more simple than the latter．The basic comparison among several multivariate decision trees iS fulfilled． |
| Key words: Rough sets univariate decision tree multivariate decision tree inductive learning relative core of attributes |
