期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：83
期号：3
出版社：Journal of Theoretical and Applied
摘要：This paper proposed a prediction model based on Fuzzy Association Rule (FARs). Present a two model; it is the integration of the Fuzzy C-Means (FCM) and Multiple Support Apriori (MS apriori). Even though, enhancing the knowledge from the large dataset, give large amount of data. So reduce some amount of data through hybrid approach of Genetic algorithm (GA) with Particle Swarm Optimation (PSO), both useful for the fuzzy association rule. Extraction of knowledge process is performed thorough betathalesemia Dataset. FCM and MSapriori model is used to extract the FARs. experimental result proves the proposed model of hybrid feature reduction with FCM-MS apriori model is effectively predict the knowledge from the large database compared to other prediction model.
