A new hybrid data mining technique using a regression case based reasoning: Application to financial forecasting

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摘要

This paper proposes a regression case based reasoning (RCBR) which applies different weights to independent variables before finding similar cases. The traditional CBR model has focused on finding similar cases from a case base without considering the importance of independent variables. Thus, when extracting similar cases the traditional CBR has put same weights on each independent variable.The proposed regression CBR (RCBR) finds a relative importance of independent variables from the relationship between independent variables and a dependent variable using a regression analysis and puts relative weights using regression coefficients on independent variables. Then, it selects nearest neighbor or similar cases using weighted independent variables through the traditional CBR machine and updates weights dynamically for the next target case and again performs the traditional CBR machine.

论文关键词:Regression case based reasoning,Artificial intelligence,Data mining,Case based reasoning,Neural network,Statistical methods,Learning techniques

论文评审过程:Available online 11 October 2005.

论文官网地址:https://doi.org/10.1016/j.eswa.2005.09.053