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| Titel: |
Analysis of the Effectiveness of the Genetic Algorithms based on Extraction of Association Rules |
| Auteur: |
Alcala-Fdez, Jesus Flugy-Pape, Nicolo Bonarini, Andrea Herrera, Francisco |
| Verschenen in: |
Fundamenta informaticae |
| Paginering: | Jaargang 98 (2010) nr. 1 pagina's 1-14 |
| Jaar: |
2010-03-15 |
| Inhoud: |
DataMining is most commonly used in attempts to induce association rules from transaction data which can help decision-makers easily analyze the data and make good decisions regarding the domains concerned. Most conventional studies are focused on binary or discrete-valued transaction data, however the data in real-world applications usually consists of quantitative values. In the last years, many researches have proposed Genetic Algorithms for mining interesting association rules from quantitative data. In this paper, we present a study of three genetic association rules extraction methods to show their effectiveness for mining quantitative association rules. Experimental results over two real-world databases are showed. |
| Uitgever: |
IOS Press |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
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