An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery

C. J. Carmona, P. González, M. J. Jesús, F. Herrera
{"title":"An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery","authors":"C. J. Carmona, P. González, M. J. Jesús, F. Herrera","doi":"10.1109/FUZZY.2009.5277412","DOIUrl":null,"url":null,"abstract":"The interpretability of the results obtained and the quality measures used both to extract and evaluate the rules are two key aspects of Subgroup Discovery. In this study, we analyse the influence of the type of rule used to extract knowledge in Subgroup Discovery, and the quality measures more adapted to the evolutionary algorithms for Subgroup Discovery developed so far. The adaptation of the NMEF-SD algorithm to extract disjunctive formal norm rules is also presented.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Fuzzy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.2009.5277412","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

The interpretability of the results obtained and the quality measures used both to extract and evaluate the rules are two key aspects of Subgroup Discovery. In this study, we analyse the influence of the type of rule used to extract knowledge in Subgroup Discovery, and the quality measures more adapted to the evolutionary algorithms for Subgroup Discovery developed so far. The adaptation of the NMEF-SD algorithm to extract disjunctive formal norm rules is also presented.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
子群发现中不同模糊规则类型的进化算法分析
所获得结果的可解释性以及用于提取和评估规则的质量度量是子组发现的两个关键方面。在本研究中,我们分析了用于提取知识的规则类型对子群发现的影响,以及更适合于目前发展的子群发现进化算法的质量度量。本文还提出了将NMEF-SD算法应用于析取形式范数规则的提取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Design and simulation of a hybrid controller for a multi-input multi-output magnetic suspension system Fuzzy CMAC structures Hybrid SVM-GPs learning for modeling of molecular autoregulatory feedback loop systems with outliers On-line adaptive T-S fuzzy neural control for active suspension systems Analyzing KANSEI from facial expressions with fuzzy quantification theory II
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1