So, Rough Set Theory has provided the frame for knowledge roughness research.
分析了基于粗糙集理论的知识粗糙性的产生、性质及实质；
We propose a new approach to multivariate decision tree construction based on knowledge roughness in rough set instead of information entropy as usual.
提出了一种基于粗糙集中知识粗糙度的构建多变量决策树的算法。
Aim to upwards points, in this paper, advance a knowledge roughness based approach to hybrid decision tree, select less knowledge roughness as tested attribute to construct decision tree.
针对以上两种决策树特点，提出了基于知识粗糙度的混合变量决策树的构造方法，选择知识粗糙度较小的分类属性来构造决策树。
The theory of rough-set points out that knowledge has granularity and defines the concept of roughness of knowledge.
在粗糙集理论中，提出知识是有粒度的并定义了知识粗糙度的概念。
In rough set theory, the concept of roughness of knowledge is defined by equivalence relation and set inclusion.
在该理论中，知识粗糙性是通过等价关系和集包含定义的。
In rough set theory, the concept of roughness of knowledge is defined by equivalence relation and set inclusion.
在该理论中，知识粗糙性是通过等价关系和集包含定义的。
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