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  Rule mining with prior knowledge -- a belief networks approach
 
 
Titel: Rule mining with prior knowledge -- a belief networks approach
Auteur: Zonglin Zhou
Huan Liu
Stan Z. Li
Chin Seng Chua
Verschenen in: Intelligent data analysis
Paginering: Jaargang 5 (2001) nr. 2 pagina's 95-110
Jaar: 2001-07-12
Inhoud: Some existing data mining methods, such as classification trees, neural networks and association rules, have the drawbacks that the user's prior knowledge cannot be easily specified and incorporated into the knowledge discovery process, and the rules mined from databases lack quantitative analyses. In this paper, we propose a belief networks method for rule mining, which takes the advantage of belief networks as the directed acyclic graph language and their function for numerical representation of probabilistic dependencies among the variables in the database, so that it can overcome the drawbacks. Since belief networks provide a natural representation for capturing causal relationship among a set of variables, our proposed method can mine more general correlation rules which can capture the relationship of more than two attribute variables. The potential application of the proposed method is demonstrated through the detailed case studies on benchmark databases.
Uitgever: IOS Press
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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