Associative classification with multiobjective Tabu search
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| Автор: | |
|---|---|
| Формат: | artículo original |
| Статус: | Versión publicada |
| Дата публикации: | 2020 |
| Описание: | 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. |
| Страна: | Portal de Revistas UCR |
| Институт: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| Язык: | Inglés |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/42438 |
| Online-ссылка: | https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/42438 |
| Ключевое слово: | combinatorial data analysis associative classification tabu search multiobjective optimization análisis de datos combinatorio clasificación asociativa búsqueda tabú optimización multiobjectivo |