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Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes

In real world, there are a lot of knowledge such as the following: most human beings that are infected by a kind of virus suffer from a corresponding disease, but a small number human beings do not. Which are the factors that negate the effects of the virus? Standard rough set method can induce simp...

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Autores principales: Honghai, Feng, Hao, Xu, Baoyan, Liu, Bingru, Yang, Zhuye, Gao, Yueli, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2006
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120026/
http://dx.doi.org/10.1007/11875581_86
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author Honghai, Feng
Hao, Xu
Baoyan, Liu
Bingru, Yang
Zhuye, Gao
Yueli, Li
author_facet Honghai, Feng
Hao, Xu
Baoyan, Liu
Bingru, Yang
Zhuye, Gao
Yueli, Li
author_sort Honghai, Feng
collection PubMed
description In real world, there are a lot of knowledge such as the following: most human beings that are infected by a kind of virus suffer from a corresponding disease, but a small number human beings do not. Which are the factors that negate the effects of the virus? Standard rough set method can induce simplified rules for classification, but cannot generate this kind of knowledge directly. In this paper, we propose two algorithms to find the factors. In the first algorithm, the typical rough set method is used to generate all the variable precision rules firstly; secondly reduce attributes and generate all the non-variable precision rules; lastly compare the variable precision rules and non-variable precision rules to generate the factors that negate the variable precision rules. In the second algorithm, firstly, induce all the variable precision rules; secondly, select the examples corresponding to the variable precision rules to build decernibility matrixes; thirdly, generate the factors that negate the variable precision rules. Three experimental results show that using the two algorithms can get the same results and the computational complexity of the second algorithm is largely less than the firs one.
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spelling pubmed-71200262020-04-06 Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes Honghai, Feng Hao, Xu Baoyan, Liu Bingru, Yang Zhuye, Gao Yueli, Li Intelligent Data Engineering and Automated Learning – IDEAL 2006 Article In real world, there are a lot of knowledge such as the following: most human beings that are infected by a kind of virus suffer from a corresponding disease, but a small number human beings do not. Which are the factors that negate the effects of the virus? Standard rough set method can induce simplified rules for classification, but cannot generate this kind of knowledge directly. In this paper, we propose two algorithms to find the factors. In the first algorithm, the typical rough set method is used to generate all the variable precision rules firstly; secondly reduce attributes and generate all the non-variable precision rules; lastly compare the variable precision rules and non-variable precision rules to generate the factors that negate the variable precision rules. In the second algorithm, firstly, induce all the variable precision rules; secondly, select the examples corresponding to the variable precision rules to build decernibility matrixes; thirdly, generate the factors that negate the variable precision rules. Three experimental results show that using the two algorithms can get the same results and the computational complexity of the second algorithm is largely less than the firs one. 2006 /pmc/articles/PMC7120026/ http://dx.doi.org/10.1007/11875581_86 Text en © Springer-Verlag Berlin Heidelberg 2006 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Honghai, Feng
Hao, Xu
Baoyan, Liu
Bingru, Yang
Zhuye, Gao
Yueli, Li
Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title_full Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title_fullStr Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title_full_unstemmed Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title_short Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes
title_sort using rough set to find the factors that negate the typical dependency of a decision attribute on some condition attributes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120026/
http://dx.doi.org/10.1007/11875581_86
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