Variable selection for hedonic model using machine learning approaches: A case study in Onondaga County, NY

► Application of machine learning regression methods to hedonic price function to select variables. ► Comparison of selection results of machine learning methods with traditional ordinary least squares method. ► Propose more practical approaches for the selection of important variables for hedonic price function.