WCOID-DG: An approach for case base maintenance based on Weighting, Clustering, Outliers, Internal Detection and Dbsan-Gmeans
作者：
Highlights：
• We propose a novel maintenance policy for case based reasoning system (WCOID-DG).
• Our aim: a large case base is transformed to a small one with improving its quality.
• We use feature weights, outliers detection methods and a new clustering technique DG.
• WCOID-GM is able to reduce both the storage requirements and search time.
• WCOID-GM is efficient in terms of getting satisfying classification accuracy.
摘要
•We propose a novel maintenance policy for case based reasoning system (WCOID-DG).•Our aim: a large case base is transformed to a small one with improving its quality.•We use feature weights, outliers detection methods and a new clustering technique DG.•WCOID-GM is able to reduce both the storage requirements and search time.•WCOID-GM is efficient in terms of getting satisfying classification accuracy.
论文关键词：Case based reasoning,Case base maintenance,Gaussian-Means clustering,Density based clustering,Outliers detection
论文评审过程：Received 19 July 2012, Revised 13 November 2012, Accepted 14 March 2013, Available online 21 March 2013.
论文官网地址：https://doi.org/10.1016/j.jcss.2013.03.006
