文章基本信息

标题：An Efficient Method for Computing All Reducts
本地全文：下载
作者：Yongguang Bao ; Xiaoyong Du ; Mingrong Deng 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2004
卷号：19
期号：3
页码：166-173
DOI：10.1527/tjsai.19.166
出版社：The Japanese Society for Artificial Intelligence
摘要：In the process of data mining of decision table using Rough Sets methodology, the main computational effort is associated with the determination of the reducts. Computing all reducts is a combinatorial NP-hard computational problem. Therefore the only way to achieve its faster execution is by providing an algorithm, with a better constant factor, which may solve this problem in reasonable time for real-life data sets. The purpose of this presentation is to propose two new efficient algorithms to compute reducts in information systems. The proposed algorithms are based on the proposition of reduct and the relation between the reduct and discernibility matrix. Experiments have been conducted on some real world domains in execution time. The results show it improves the execution time when compared with the other methods. In real application, we can combine the two proposed algorithms.
关键词：machine learning ; rough sets ; attribute reduct ; #English#