Title
A parallel approximate rule extracting algorithm based on the improved discernibility matrix
Abstract
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.
Year
DOI
Venue
2004
null
Lecture Notes in Artificial Intelligence
Keywords
DocType
Volume
null
Conference
3066
Issue
ISSN
Citations 
null
0302-9743
7
PageRank 
References 
Authors
0.60
4
6
Name
Order
Citations
PageRank
Yong Liu170.60
Congfu Xu213115.71
Yunhe Pan3122384.09
L Yong470.60
CF Xu570.60
YH Pan6101.19