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 |
| |
Affiliation: | 1. Department of Economics, Democritus University of Thrace, Greece;2. Department of Economics, Pretoria University, South Africa;1. Office of the Comptroller of the Currency. Credit Risk Analysis Division., 400 7th Street SW, Washington, DC 20219, USA;2. UNC Charlotte and Office of the Comptroller of the Currency. Credit Risk Analysis Division., 400 7th Street SW, Washington, DC 20219, USA |
| |
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. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|