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frbs: Fuzzy rule-based systems for classification and regression in R
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نویسنده
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riza l.s. ,bergmeir c. ,herrera f. ,benítez j.m.
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منبع
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journal of statistical software - 2015 - دوره : 65 - - کد همایش:
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چکیده
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Fuzzy rule-based systems (frbss) are a well-known method family within soft com- puting. they are based on fuzzy concepts to address complex real-world problems. we present the r package frbs which implements the most widely used frbs models,namely,mamdani and takagi sugeno kang (tsk) ones,as well as some common variants. in ad- dition a host of learning methods for frbss,where the models are constructed from data,are implemented. in this way,accurate and interpretable systems can be built for data analysis and modeling tasks. in this paper,we also provide some examples on the usage of the package and a comparison with other common classification and regression methods available in r. © 2015,american statistical association. all rights reserved.
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کلیدواژه
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Fuzzy inference systems; Fuzzy neural networks; Fuzzy sets; Genetic fuzzy systems; Soft computing
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آدرس
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department of computer science and artificial intelligence,e.t.s. de ingenierías informática y de telecomunicación,citic-ugr,imuds,university of granada,granada,18071, Spain, department of computer science and artificial intelligence,e.t.s. de ingenierías informática y de telecomunicación,citic-ugr,imuds,university of granada,granada,18071, Spain, department of computer science and artificial intelligence,e.t.s. de ingenierías informática y de telecomunicación,citic-ugr,imuds,university of granada,granada,18071, Spain, department of computer science and artificial intelligence,e.t.s. de ingenierías informática y de telecomunicación,citic-ugr,imuds,university of granada,granada,18071, Spain
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Authors
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