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Content Provider | IEEE Xplore Digital Library |
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Author | Saeki, T. Nishiura, T. Kato, Y. |
Copyright Year | 2011 |
Description | Author affiliation: Interdisciplinary Faculty of Science and Engineering, Shimane University, 1060 Nishikawatsu-cho, Matsue city, 690-8504, Japan (Nishiura, T.; Kato, Y.) || Faculty of Engineering, Yamaguchi University, 2-16-1 Tokiwadai, Ube city, 755-8611, Japan (Saeki, T.) |
Abstract | Rough sets theory is often used for extracting ifthen rules from categorical data sets with an objective function. In the conventional rough sets theory, the decision matrix method is known as one of the method extracting the rules. However, devising an efficient algorithm for the decision matrix method has seldom been reported to date. Consequently, this paper studies the process of reducing the decision matrix, finds several properties useful for the rule extraction, and proposes an effective algorithm for the extraction. The algorithm is implemented in a piece of software and a simulation experiment is conducted to compare the reduced time of the software base on the proposed algorithm with that of LEM2 software which is open to the public on the Internet, and is widely used throughout the world. As the results, the newly developed software is confirmed to perform exceptionally well under taxing conditions. |
Starting Page | 3190 |
Ending Page | 3194 |
File Size | 399243 |
Page Count | 5 |
File Format | |
ISBN | 9781457706523 |
ISSN | 1062922X |
e-ISBN | 9781457706530 |
DOI | 10.1109/ICSMC.2011.6084160 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-10-09 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Software Software algorithms Rough sets Data mining Absorption Data models Approximation methods Decision Matrix Rough Sets Rule Extraction |
Content Type | Text |
Resource Type | Article |
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