Associative classification with multiobjective Tabu search
保存先:
| 著者: | |
|---|---|
| フォーマット: | artículo original |
| 状態: | Versión publicada |
| 出版日付: | 2020 |
| その他の書誌記述: | 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. |
| 国: | Portal de Revistas UCR |
| 機関: | Universidad de Costa Rica |
| Repositorio: | Portal de Revistas UCR |
| 言語: | Inglés |
| OAI Identifier: | oai:archivo.portal.ucr.ac.cr:article/42438 |
| オンライン･アクセス: | https://archivo.revistas.ucr.ac.cr/index.php/matematica/article/view/42438 |
| キーワード: | combinatorial data analysis associative classification tabu search multiobjective optimization análisis de datos combinatorio clasificación asociativa búsqueda tabú optimización multiobjectivo |