Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data
Housing price valuation is one of most important trading decisions. This study uses machine learning to develop housing price prediction models. This study analyzes the housing data of 5359 townhouses in Fairfax County, VA. The 10-fold cross-validation was applied to C4.5, RIPPER, Bayesian, and AdaBoost. RIPPER outperformed these other housing price prediction models in all tests.
machine learning algorithms housing price prediction model c4.5 ripper adaboost housing price index nave bayesian