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머신러닝을 활용한 중고 자동차의 가격 예측 모델에 관한 연구: 국내 브랜드를 중심으로A Study on Price Prediction Model of Used Cars Using Machine Learning: Focus on Domestic Brands

Other Titles
A Study on Price Prediction Model of Used Cars Using Machine Learning: Focus on Domestic Brands
Authors
임승준이정호류춘호
Issue Date
Aug-2023
Publisher
한국경영과학회
Keywords
Used Car Price; Regression Based Machine Learning; Decision Tree Based Machine Learning
Citation
한국경영과학회지, v.48, no.3, pp.1 - 14
Journal Title
한국경영과학회지
Volume
48
Number
3
Start Page
1
End Page
14
URI
https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/31690
ISSN
1225-1119
Abstract
The domestic used car market continues to grow along with the used car online platform. The used car online platform discloses vehicle specifications, accident history, inspection history, and detailed options to consumers. Most of the studies for predicting used car prices were studies using vehicle specifications. In addition, the relationship between the mileage and period of use of the vehicle and the used car price tended to appear nonlinear. In order to solve this problem, recent studies have attempted to reduce Cost Function using Machine Learning models. Accordingly, this study sequentially executed Regression based and Decision Tree based Machine Learning models using vehicle specifications and vehicle options. The implications of this study were, first, to make the most of their advantages by continuously executing two types of Machine Learning models. Second, which of the vehicle's specifications and option variables affects the price prediction of used cars, and the influence and direction of these variables were confirmed. This will help solve the problem caused by unfair information among used car sales officials.
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