Associative classification with multiobjective Tabu search

This paper presents an application of Tabu Search algorithm to association rule mining. We focus our attention specifically on classification rule mining, often called associative classification, where the consequent part of each rule is a class label. Our approach is based on seek a rule set handle...

ver descrição completa

Detalhes bibliográficos
Autor: Beausoleil, Ricardo P.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:Costa Rica
Recursos:Universidad de Costa Rica
Repositorio:Portal de Revistas UCR
Idioma:inglés
OAI Identifier:oai:portal.ucr.ac.cr:article/42438
Acesso em linha:https://revistas.ucr.ac.cr/index.php/matematica/article/view/42438
Access Level:acceso abierto
Palavra-chave:combinatorial data analysis
associative classification
tabu search
multiobjective optimization
análisis de datos combinatorio
clasificación asociativa
búsqueda tabú
optimización multiobjectivo
Descrição
Resumo:This paper presents an application of Tabu Search algorithm to association rule mining. We focus our attention specifically on classification rule mining, often called associative classification, where the consequent part of each rule is a class label. Our approach is based on seek a rule set handled as an individual. A Tabu search algorithm is used to search for Pareto-optimal rule sets with respect to some evaluation criteria such as accuracy and complexity. We apply a called Apriori algorithm for an association rules mining and then a multiobjective tabu search to a selection rules. We report experimental results where the effect of our multiobjective selection rules is examined for some well-known benchmark data sets from the UCI machine learning repository.