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

Jae Joon Ahn, Hyun Woo Byun, Kyong Joo Oh, Tae Yoon Kim

Research output: Contribution to journalArticle

32 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)8369-8379
Number of pages11
JournalExpert Systems with Applications
Volume39
Issue number9
DOIs
Publication statusPublished - 2012 Jul 1

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Genetic algorithms
Linear regression
Artificial intelligence

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

Cite this

Ahn, Jae Joon ; Byun, Hyun Woo ; Oh, Kyong Joo ; Kim, Tae Yoon. / Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. In: Expert Systems with Applications. 2012 ; Vol. 39, No. 9. pp. 8369-8379.
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Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting. / Ahn, Jae Joon; Byun, Hyun Woo; Oh, Kyong Joo; Kim, Tae Yoon.

In: Expert Systems with Applications, Vol. 39, No. 9, 01.07.2012, p. 8369-8379.

Research output: Contribution to journalArticle

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