Rough set theory and its practice in knowledge discovery

被引：0

作者：

Fu, SX ^{[1
]}

Lu, ZX ^{[1
]}

Lu, HM ^{[1
]}

Li, YD ^{[1
]}

机构：

[1] Tsing Hua Univ, Automat Dept, Beijing 100084, Peoples R China

来源：

PROCEEDINGS OF THE 3RD WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-5 | 2000年

关键词：

rough set; vagueness; knowledge discovery in database (KDD); approximation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

As an effect mathematic tool to deal with the vagueness and uncertainty, the rough set theory has got much attention in the fields of artificial intelligence, pattern recognition, knowledge process and so on, this paper introduces the Pawlak rough set theory model and the generalized rough set theory model, discusses the general methods used in knowledge discovery in database. and measures the plausibility with the generalized model. Finally, it also reviews the research and applications briefly.

引用

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页码：2535 / 2539

页数：5

共 10 条

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