教師資料查詢 | 類別: 期刊論文 | 教師: 陳俊豪 CHUN-HAO CHEN (瀏覽個人網頁)

標題:MULTI-OBJECTIVE GENETIC-FUZZY DATA MINING
學年101
學期1
出版(發表)日期2012/10/01
作品名稱MULTI-OBJECTIVE GENETIC-FUZZY DATA MINING
作品名稱(其他語言)
著者Chen, Chun-Hao; Hong, Tzung-Pei; Tseng, Vincent S.; Chen, Lien-Chin
單位淡江大學資訊工程學系
出版者Kumamoto: I C I C International
著錄名稱、卷期、頁數International Journal of Innovative Computing, Information and Control 8(10A), pp.6551-6568
摘要Many approaches have been proposed for mining fuzzy association rules.The membership functions, which critically influence the fi nal mining results, are diffi cult to defi ne. In general, multiple criteria are considered when defi ning membership functions. In this paper, a multi-objective genetic-fuzzy mining algorithm is proposed for extracting membership functions and association rules from quantitative transactions.Two objective functions are used to find the Pareto front. The fi rst one is the suitability of membership functions. It consists of the coverage factor and the overlap factor and is used to avoid two unsuitable types of membership function. The second one is the total
number of large 1-itemsets from a given set of minimum support values. Experimental results show the effectiveness of the proposed approach in fi nding the Pareto-front membership functions.
關鍵字Multi-objective optimization; Genetic algorithm; Fuzzy set; Fuzzy association rules; Data mining
語言英文
ISSN1349-4198
期刊性質國外
收錄於SCI
產學合作
通訊作者Hong, Tzung-Pei
審稿制度
國別日本
公開徵稿
出版型式紙本
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