A parallel approximate rule extracting algorithm based on the improved discernibility matrix

被引：0
|
作者：
Yong, L [1 ]
Xu, CF [1 ]
Pan, YH [1 ]
机构：
[1] Zhejiang Univ, Inst Artificial Intelligence, Hangzhou 310027, Peoples R China
来源：
ROUGH SETS AND CURRENT TRENDS IN COMPUTING | 2004年 / 3066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：
A parallel rule-extracting algorithm based on the improved discernibility matrix [2] is proposed, by this way, a large amount of raw data can be divided into some small portions to be processed in parallel. The confidence factor is also introduced to the rule sets to obtain the uncertainty rules. The most important advantage of this algorithm is that it does not need to calculate the discernibility matrix corresponding to these overall data.
引用
收藏
页码：498 / 503
页数：6
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