Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting

Authors:
Jae Joon Ahn;Hyun Woo Byun;Kyong Joo Oh;Tae Yoon Kim
Affiliations:
Department of Information and Industrial Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, South Korea;Department of Information and Industrial Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, South Korea;Department of Information and Industrial Engineering, Yonsei University, 134, Shinchon-Dong, Seodaemun-Gu, Seoul 120-749, South Korea;Department of Statistics, Keimyung University, Daegu 704-701, South Korea
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

This study considers real estate appraisal forecasting problem. While there is a great deal of literature about use of artificial intelligence and multiple linear regression for the problem, there has been always controversy about which one performs better. Noting that this controversy is due to difficulty finding proper predictor variables in real estate appraisal, we propose a modified version of ridge regression, i.e., ridge regression coupled with genetic algorithm (GA-Ridge). In order to examine the performance of the proposed method, experimental study is done for Korean real estate market, which verifies that GA-Ridge is effective in forecasting real estate appraisal. This study addresses two critical issues regarding the use of ridge regression, i.e., when to use it and how to improve it.