Bayesian Belief Network untuk Menghasilkan Fuzzy Association Rules

Autor: Rolly Intan, Oviliani Yenty Yuliana, Dwi Kristanto
Jazyk: English<br />Indonesian
Rok vydání: 2010
Předmět:
Zdroj: Jurnal Teknik Industri, Vol 12, Iss 1, Pp 55-60 (2010)
Druh dokumentu: article
ISSN: 1411-2485
Popis: Bayesian Belief Network (BBN), one of the data mining classification methods, is used in this research for mining and analyzing medical track record from a relational data table. In this paper, a mutual information concept is extended using fuzzy labels for determining the relation between two fuzzy nodes. The highest fuzzy information gain is used for mining fuzzy association rules in order to extend a BBN. Meaningful fuzzy labels can be defined for each domain data. For example, fuzzy labels of secondary disease and complication disease are defined for a disease classification. The implemented of the extended BBN in a application program gives a contribution for analyzing medical track record based on BBN graph and conditional probability tables.
Databáze: Directory of Open Access Journals