MACHINE LEARNING FOR PROPERTY PRICE PREDICTION AND PRICE VALUATION: A SYSTEMATIC LITERATURE REVIEW
DOI:
https://doi.org/10.21837/pm.v19i17.1018Keywords:
machine learning, real estate, property price prediction, valuationAbstract
Machine learning is a branch of artificial intelligence that allows software applications to be more accurate in its data predicting, as well as to predict current performance and improve for future data. This study reviews published articles with the application of machine learning techniques for price prediction and valuation. Authors seek to explore optimal solutions in predicting the property price indices, that will be beneficial to the policymakers in assessing the overall economic situation. This study also looks into the use of machine learning in property valuation towards identifying the best model in predicting property values based on its characteristics such as location, land size, number of rooms and others. A systematic review was conducted to review previous studies that imposed machine learning as statistical tool in predicting and valuing property prices. Articles on real estate price prediction and price valuation using machine learning techniques were observed using electronics database. The finding shows the increasing use of this method in the real estate field. The most successful machine learning algorithms used is the Random Forest that has better compatibility to the data situation.Downloads
References
Begel, A. (2019). Software Engineering for Machine Learning: A Case Study. Microsoft Research, 1-10.
Borde, S., & Rane, A. (2017). Real Estate Investment Advising Using Machine Learning. Journal of Engineering and Technology (IRJET), 04(03), 1821-1825.
Chardon, I., & Javier, F. (2018). Housing Prices: Testing Machines Learning Methods. 2-15.
Christodoulou, E. (2019). A Systematic Review shows no Performance Benefit of Machine Learning over Logistics Regression for Clinical Prediction Models. Journal of Clinical Epidemiology, 110, 12-22.
Crosby, H., & Davis, P. (2016). A Spatio-Temporal, Gaussian Process Regression, Real-Estate Price Predictor. 3-6.
Dellstad, M. (2018). Comparing Three Machine Learning Algorithms in the task of Appraising Commercial Real Estate. KTH Royal Institute of Technology.
Di, N. F. M., Satari, S. Z., & Zakaria, R. (2017). Real estate value prediction using multivariate regression models
Ghassemi, M. (2018). A Review of Challenges and Opportunities in Machine Learning for Health.
Gu, G., & Xu, B. (2017). Housing Market Hedonic Price Study Based on Boosting Regression Tree. Advanced Computational Intelligence and Informatics, 21(6).
Horino, H., & Nonaka, H. (2017). Development of an Entropy-Based Feature Selection Method on Real Estate. Industrial & Engineering Management, 2351-2355.
Ja’afar, N. S., & Mohamad, J. (2021). Application of Machine Learning in Analysing Historical and Non-Historical Characteristics of Heritage Pre-War Shophouses. Journal of the Malaysian Institute of Planners, 19(2), 72-84.
Jordan, M. I. (2015). Machine learning: Trends, Perspectives and Prospects. Journal of Electrical Engineering and Computer, 349(6245), 255-260.
Kamalov, F., & Gurrib, I. (2021). Financial Forecasting with Machine Learning: Price Vs Return. Journal of Computer Science, 17(3), 251-264.
Kilibarda, M. (2018). Estimating the Performance of Random Forest versus Multiple Regression for Predicting Prices of the Apartments. Geo-Information, 1-16.
Lalu, M. M., Li, T., & Loder, E. W. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Journal of Surgery, 88, 1-11.
Ma, Y., & Zhang, Z. (2018). Estimating Warehouse Rental Price using Machine Learning Techniques. Journal of Computers Communications and Control, 13(April), 235250.
Maalel, A. (2011). The Contribution of Machine Learning to Analyze and Evaluate the Safety of Automated Transport Systems. (May 2016), 1-7.
Mayer, M., Bourassa, S. C., & Hoesli, M. (2019). Estimation and Updating Methods for Hedonic Valuation. Journal of European Real Estate Research.
Mccluskey, W. J., & Daud, D. (2014). Boosted Regression Trees an Application for the Mass Appraisal of Residential Property in Malaysia. Journal of Financial Management of Property and Construction, 19(2), 152-167.
Medrano, C., & Delgado, J. (2019). Estimation of missing prices in real-estate market agent-based simulations with machine learning and dimensionality reduction. 7.
Mohamad, J., & Ismail, S. (2019). Capabilities of Revealed Preference Method for Heritage Property Valuation. Journal of the Malaysia Institute of Planners, 17(1), 377-379.
Mohamad, J., Ja’afar, S., & Ismail, S. (2020). Heritage Property Valuation using Machine Learning Algorithms. Annual Pacific Rim Real Estate Society, 1-12.
Mohd, T., Masrom, S., & Johari, N. (2019). Machine Learning Housing Price Prediction in Selangor, Malaysia. Recent Technology and Engineering (RTE), 8(2), 542-546.
Mu, J., Wu, F., & Zhang, A. (2014). Housing Value Forecasting Based on Machine Learning Methods. Abstract and Applied Analysis, 2014, 1-7.
Nejad, M. Z., Lu, J., & Behbood, V. (2017). Applying Dynamic Bayesian Tree in Property Sales Price Estimation.
Niu, W., & Feng, Z. (2019). Neural Network, Extreme Learning Machine and Support Vector Machine in Deriving Operation Rule of Hydropower Reservoir. Journal of Water, 11(88). https://doi.org/10.3390/w11010088
Oladunni, T. (2016). Hedonic Housing Theory A Machine Learning Investigation. Journal of Machine Learning and Application, (December).
Oladunni, T., & Sharma, S. (2015). Predictive Real Estate Multiple Listing System Using MVC Architecture and Linear Regression 1 Introduction.
Olanrewaju, A. L., & Lim, X. Y. (2018). Factors Affecting Housing Prices in Malaysia: Analysis of the Supply Side. Journal of the Malaysian Institute of Planners, 16(2), 225-235.
Pagourtzi, E., Assimakopoulos, V., & Thomas, H. (2003). Real Estate Appraisal: A review of Valuation Methods. Property Investment & Finance, 21(4), 383-401.
Park, B., & Kwon, J. (2015). Using Machine Learning Algorithms for Housing Price Prediction Fairfax. Journal of Expert System with Applications, 42(6), 2928-2934.
Phan, T. D. (2019). Housing Price Prediction using Machine Learning Algorithms : The Case of Melbourne, Australia. Machine Learning and Data Engineering, 35-42.
Pow, N., & Janulewicz, E. (2018). Applied Machine Learning Project 4 Prediction of Real Estate Property Prices in Montreal.
Sarip, A. G. (2015). Fuzzy Logic Application for House Price Prediction. Journal of Property Sciences, 5(1), 24-30.
Schernthanner, H. (2011). Spatial modeling and geovisualization of rental prices for real estate portals.
Shinde, N., & Gawande, K. (2018). Valuation of House Prices using Predictive Techniques. Journal of Advances in Electronics Computer Science, 5(6), 34-40.
Song, Y., & Lu, Y. (2015). Decision Tree Methods : Applications for Classification and Prediction. Journal of Biostatistics in Psychiatry, 27(2), 130-136.
Trawinski, B., & Telec, Z. (2017). Comparison of Expert Algorithms with Machine Learning Models for Real Estate Appraisal. Journal of Science and Technology.
Valle, M. A., & Crespo, R. (2016). Property Valuation using Machine Learning Algorithms. Journal of Modelling and Simulation, 97-105.
Varma, A., & Sarma, A. (2018). House Price Prediction Using Machine Learning And Neural Networks. Journal of Inventive Communication and Computational Technologies (ICICCT), 1936-1939.
Downloads
Published
How to Cite
Issue
Section
License
Copyright & Creative Commons Licence
eISSN: 0128-0945 © Year. The Authors. Published for Malaysia Institute of Planners. This is an open-access article under the CC BY-NC-ND license.
The authors hold the copyright without restrictions and also retain publishing rights without restrictions.
