NDLI: Algoritmos Genéticos Multi-Objetivos Na Mineração De Regras Interessantes E Precisas

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Algoritmos Genéticos Multi-Objetivos Na Mineração De Regras Interessantes E Precisas

Content Provider	Semantic Scholar
Author	Oliveira, Gina M. B. Takiguti, Maria Cazuho Saito Martins, Luiz Gustavo Almeida
Copyright Year	2016
Abstract	 This work evaluates the use of multi-objective genetic algorithms (MOGA) in the mining of accurate and interesting rules. For this, a program was implemented based on the MOGA technique called nondominated sorting genetic algorithm (NSGA), which was applied in the database Zoo of public domain. The results of our experiments had been compared with those generated by a standard genetic algorithm in order to identify the benefits related to the multi-objective approach. Keyword Multi-objective genetic algorithms, rules mining, data mining. Resumo Este trabalho avalia o uso de algoritmos genéticos multi-objetivos (AGMO) no processo de mineração de regras precisas e interessantes. Implementou-se um programa baseado na técnica de AGMO conhecida como nondominated sorting genetic algorithm, o qual foi aplicado na base de dados de domínio público Zoo. Os resultados foram comparados com aqueles gerados por um algoritmo genético padrão, a fim de identificar as melhorias obtidas pela adoção de uma abordagem multi-objetivos. Palavras-chave Algoritmos genéticos multi-objetivos, extração de regras, mineração de dados.
Starting Page	1
Ending Page	6
Page Count	6
File Format	PDF HTM / HTML
DOI	10.21528/CBRN2007-128
Alternate Webpage(s)	http://abricom.org.br/wp-content/uploads/2016/03/50100128.pdf
Alternate Webpage(s)	https://doi.org/10.21528/CBRN2007-128
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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