Mining quantitative data based on tolerance rough set model

被引：0
|
作者：
Lee, HS [1 ]
Shen, PD
Chyr, WL
Tseng, WK
机构：
[1] Natl Taiwan Ocean Univ, Dept Shipping & Transportat Management, Chilung 202, Taiwan
[2] Ming Chung Univ, Dept Informat Management, Taipei, Taiwan
[3] Ming Chung Univ, Grad Sch Management, Taipei, Taiwan
来源：
KNOWLEDGE-BASED INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, PT 1, PROCEEDINGS | 2005年 / 3681卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Rough set theory has been widely used in knowledge acquisition. However, In conventional application of rough set to numeric data, data must be pre-classified. In this paper, a different approach is introduced to deal with numeric data. We develop a mining algorithm based on fuzzy sets and tolerance rough set model, which offers a way of relating data in their semantics.
引用
收藏
页码：359 / 364
页数：6
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