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

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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. (C) 2005 Elsevier Ltd. All rights reserved.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2006
Language
English
Article Type
Article
Keywords

KNOWLEDGE DISCOVERY TECHNIQUES; STOCK-MARKET; PREDICTION

Citation

EXPERT SYSTEMS WITH APPLICATIONS, v.31, no.2, pp.329 - 336

ISSN
0957-4174
DOI
10.1016/j.eswa.2005.09.053
URI
http://hdl.handle.net/10203/86168
Appears in Collection
RIMS Journal Papers
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