Weighted Fuzzy Similarity Relations in Case-Based Reasoning: a Case Study in Classification

被引：0

作者：

Sandri, Sandra ^{[1
]}

Mendonca, Jonas ^{[1
]}

Martins-Bede, Flavia ^{[1
]}

Guimaraes, Ricardo ^{[2
]}

Carvalho, Omar ^{[3
]}

机构：

[1] INPE, Sao Jose Dos Campos, SP, Brazil

[2] Lab Geoprocessamento Inst, Evandro Chagas SVS MS, Belem, Brazil

[3] Ctr Pesquisas Rene Rachou FIOCRUZ, Horizont, MG, Brazil

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE) | 2012年

基金：

巴西圣保罗研究基金会;

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes a fuzzy similarity relation approach to Case-Based Reasoning. Residuated implication operators are used to create a fuzzy resemblance relation between cases, modeling the CBR basic principle "the more similar the problem descriptions are, the more similar the solution descriptions are" as a fuzzy gradual rule. We take the classification of Schistosomiasis prevalence estimation in a region of Brazil as case study, in order to investigate the effects in such a framework of weighting cases individually in classification tasks, considering a set of training strategies.

引用

页数：7

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