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 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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Conference Date 2014/1/23(1days)
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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
Date of Issue