Data mining is an important problem in KDD, and Rough set as a theory of set with fuzzy boundary is widely applied to infer classification rules from decision system.
数据挖掘是知识发现领域的一个重要问题，粗糙集理论是一种具有模糊边界的数据挖掘方法，它被广泛应用于决策系统的分类规则提取中。
This paper analysis three different kinds of improved algorithms based onthe K-NN classification:(1) Editing technique, (2) Boundary extraction, (3) Boundarypatching.
本文研究三种在近邻分类法基础上的改进算法：（1）编辑技术，（2）边界抽取，（3）边界补缀。
I gives the classification of simple boundary singularities under right equivalence.
给出了简单边界奇点在右等价下的分类。
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