Learning and applications based on rough set theory

被引：0
|
作者：
Cai, D [1 ]
机构：
[1] Univ Glasgow, Dept Comp Sci, Glasgow G12 8RZ, Lanark, Scotland
来源：
INTELLIGENT TECHNIQUES AND SOFT COMPUTING IN NUCLEAR SCIENCE AND ENGINEERING | 2000年
关键词：
D O I：
10.1142/9789812792631_0013
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Data mining is emerging as a key enabling technology for a variety of scientific, engineering, medical and business applications. Data mining over large data sets can take a prohibitive amount of time due to the time complexity of the algorithm. Drawing inspiration from the technique "dropping condition attributes" in machine learning, we present scalable parallel data mining algorithms. Our methods are illustrated by a decision table KRS (from a Knowledge Representation System).
引用
收藏
页码：108 / 115
页数：8
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