Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data

By Byeonghwa Park, Jae Kwon Bae. Expert systems with applications, 2015

358 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/528f0ce730b0607cc6107d672aec344aaaae1b24

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Jengei Hong
2. Woo-sung Kim
3. Heeyoul Choi

In Electrical and Electronic Engineering

1. Jengei Hong
2. Woo-sung Kim
3. Heeyoul Choi

Citations in the corpus

• A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA (2020, methodology): “Park and Bae (2015) developed a housing price appraisal model based on machine learning algorithms, such as C4.5, RIPPER, Naïve Bayesian, and AdaBoost, and analyzed the housing data for Fairfax County, Virginia, USA.”