Effects of neighborhood streetscape on the single-family housing price: Focusing on nonlinear and interaction effects using interpretable machine learning

Previous studies using the conventional Hedonic Price Model to predict existing housing prices may have limitations in addressing the relationship between house prices and streetscapes as visually perceived at the human eye level, due to the constraints of streetscape estimations. Therefore, in this...

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Bibliographic Details
Published in:PloS one 2025-05, Vol.20 (5), p.e0323495
Main Authors: Han, Jaewon, Woo, Ayoung, Lee, Sugie
Format: Article
Language:English
Subjects:
Algorithms
Big Data
Biology and Life Sciences
Commerce
Computer and Information Sciences
Computer vision
Deep learning
Earth Sciences
Ecology and Environmental Sciences
Economic aspects
Engineering and Technology
Houses
Housing
Housing - economics
Housing prices
Housing, Single family
Humans
Identification methods
Influence
Learning algorithms
Machine Learning
Neighborhood
Neighborhood Characteristics
Neighborhoods
Pedestrians
Perceptions
Prices and rates
Regression analysis
Regression models
Republic of Korea
Residence Characteristics
Social Sciences
Urban planning
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