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

TitleA new hybrid data mining technique using a regression case based reasoning: Application to financial forecasting
Publication TypeJournal Article
Year of Publication2005
AuthorsChun S., Park Y.
JournalExpert Systems with Applications
Volume31
Issue2
Start Page329
Paginationperiodically
Date Published08/2006
Type of ArticleOriginal Research Article
ISSN0957-4174
Keywordsartificial intelligence, Case based reasoning, Data mining, Learning techniques, Neural network, Regression case based reasoning, Statistical methods
Abstract

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.

URLhttp://www.sciencedirect.com/science/article/pii/S0957417405002198#!
Refereed DesignationNon-Refereed