Case Base Maintenance for Improving Prediction Quality

Autor:	Rushed Kanawati, Sylvie Salotti, Farida Zehraoui
Rok vydání:	2007
Předmět:	Reduction (complexity) Noise Computer science media_common.quotation_subject Case-based reasoning Quality (business) Data mining computer.software_genre computer Case base Expert system media_common
Zdroj:	Case-Based Reasoning Research and Development ISBN: 9783540404330 ICCBR
DOI:	10.1007/3-540-45006-8_53
Popis:	We propose a new case base maintenance strategy which allows the improvement of the prediction quality of CBR system. This strategy combines the learning of new selected cases, the reduction of the use of noise cases, and the removal of not useful cases. We describe in this paper the case based reasoning system, in which we have associated new measurements for the source cases. These measurements vary with the use of the cases to get target cases solutions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::6451bc9a655fb92356ebbf338d3887ad https://doi.org/10.1007/3-540-45006-8_53 Zobrazit plný text záznamu