Presentation | 2014/1/23 Studies on If-then Rule Induction by Statistical Rough Set Method and its Simulation Experiment Yuichi Kato, Tetsuro Saeki, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Rough Sets theory is widely used as a method for estimating and/or inducing knowledge structure of if-then rules from various decision tables. This paper presents results of a retest on rough set rule induction ability of the conventional method by the use of simulation data sets after summarizing it briefly and points out the problems of the conventional one. We here propose a new rule induction method based on a statistical view and its efficient algorithm (STRIM). The validity and usefulness of STRIM is confirmed by applying to the simulation data sets. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | if-then rule / lower and upper approximation / statistical test / algorithm |
Paper # | SS2013-63,MSS2013-66 |
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Committee | SS |
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Conference Date | 2014/1/23(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Software Science (SS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Studies on If-then Rule Induction by Statistical Rough Set Method and its Simulation Experiment |
Sub Title (in English) | |
Keyword(1) | if-then rule |
Keyword(2) | lower and upper approximation |
Keyword(3) | statistical test |
Keyword(4) | algorithm |
1st Author's Name | Yuichi Kato |
1st Author's Affiliation | Interdisciplinary Faculty of Science and Engineering, Shimane University() |
2nd Author's Name | Tetsuro Saeki |
2nd Author's Affiliation | Faculty of Engineering, Yamaguchi University |
Date | 2014/1/23 |
Paper # | SS2013-63,MSS2013-66 |
Volume (vol) | vol.113 |
Number (no) | 422 |
Page | pp.pp.- |
#Pages | 6 |
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