An Optimizing Method based on Water-Filling for Case Attribute Weight
Case retrieve is the key link in Case-Based Reasoning(CBR)system, and the distribution of attribute weights affects the retrieval accuracy directly. However, the traditional retrieval methods do not pay much attention to the weights distribution which led to low retrieval efficiency. In this paper, a new method based on Water-Filling principle in wireless communication field is proposed to optimize the case attribute weights. Regarding every single attribute in the case base as a sub channel, then calculates the importance of each case attribute by analyzing the data volatility with the Water-Filling principle. To prove the availability of the method, a glass identification dataset from the UCI database is used for a simulation experiment and the result illustrates that the new method could get a better and more accurate retrieval result compared with the traditional methods. The method could dig the inner information of each case attribute, and could assign proper weight to each attribute, which improves the retrieval accuracy and proves that the method the paper introduced is effective for CBR system.
Case-based reasoning case retrieve Water-Filling case attribute weights
ZHAO Hui YAN Ai-jun ZHANG Chun-xiao WANG Pu
College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing, 100124, China
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
3467-3470
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）