Abstract
The real estate industry relies heavily on accurately predicting the price of a house based on numerous factors such as size, location, amenities, and season. In this study, we explore the use of machine learning techniques for predicting house prices by considering both visual cues and estate attributes. We collected a dataset (REPD-3000) of 3000 houses across 74 cities in the USA and annotated 14 estate attributes and five visual images for each house's exterior, interior-living room, kitchen, bedroom, and bathroom. We extracted features from the input images using convolutional neural network (CNN) and fed them along with the estate attributes into a multi-kernel deep learning regression model to predict the house price. Our model outperformed baseline models in extensive experiments, achieving the best result with a mean absolute error (MAE) of 16.60. We compared our model with a multi-kernel support vector regression and analyzed the impact of incorporating individual feature sets. In future, we plan to address class imbalance by having the same number of houses in each class and explore feature engineering for improving the model's performance.
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References
Abdul Rahman, N.S., Ubaidullah, N.H., Ibrahim, I.: House price prediction using a machine learning model: a survey of literature. Int. J. Mod. Educ. Comput. Sci. 12(6), 46–54 (2020). https://doi.org/10.5815/ijmecs.2020.06.04
Ahmed, E.H. and Moustafa, M.: House Price Estimation from Visual and Textual Features. In: Proceedings of the 8th International Joint Conference on Computational Intelligence (2016), https://doi.org/10.5220/0006040700620068
Bin Khamis, A., Kamarudin, N.: Comparative study on estimate house price using statistical and neural network model. Int. J. Sci. Technol. Res. 3(12), 126–131 (2014)
Burse, S., Anjaria, D., Balaji, H.: Housing price prediction using linear regression. Int. J. Emerg. Technol. Innov. Res. 8(10), 9–12 (2021)
Chang, E.: What Is A Homeowners Association, or HOA?, Bankrate. https://www.bankrate.com/real-estate/what-is-an-hoa/ (accessed Jul. 13, 2022)
Chen, N.: House price prediction model of Zhaoqing city based on correlation analysis and multiple linear regression analysis. Wirel. Commun. Mob. Comput. 2022, 9590704 (2022)
Gupta, A., Dargar, S.K. and Dargar, A.: House Prices Prediction Using Machine Learning Regression Models. In: 2022 IEEE 2nd International Conference on Mobile Networks and Wireless Communications (ICMNWC), Tumkur, Karnataka, India, 2022, pp. 1–5, https://doi.org/10.1109/ICMNWC56175.2022.10031728
Imran, I., Zaman, U., Waqar, M., Zaman, A.: Using machine learning algorithms for housing price prediction: the case of Islamabad housing data. Soft Comput. Mach. Intell. J. (2021). https://doi.org/10.22995/scmi.2021.1.1.03
Kumar, G.K., Rani, D.M., Koppula, N., and Ashraf, S.: Prediction of House Price Using Machine Learning Algorithms. In: 2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), Jun. 2021, https://doi.org/10.1109/icoei51242.2021.9452820
Lathuilière, S., Mesejo, P., Alameda-Pineda, X., Horaud, R.: A comprehensive analysis of deep regression. IEEE Trans. Pattern Anal. Mach. Intell. 42(9), 2065–2081 (2020). https://doi.org/10.1109/TPAMI.2019.2910523
Mora-García, R., Cespedes-Lopez, M. and Pérez-Sánchez, V.: Figure 7 from housing price prediction using machine learning algorithms in COVID-19 times. In: IEEE Semantic Scholar, Land, vol. null, no. null, pp. null, 1970. https://doi.org/10.1109/SSC.1970.123456789
Mysore, S.: Prediction of house prices using machine learning. Int. J. Res. Appl. Sci. Eng. Technol. 10(6), 1780–1785 (2022). https://doi.org/10.22214/ijraset.2022.44033
Nur, A., Ema, R., Taufiq, H., Firdaus, W.: Modeling house price prediction using regression analysis and particle swarm optimization case study : Malang, East Java, Indonesia. Int. J. Adv. Comput. Sci. Appl. (2017). https://doi.org/10.14569/ijacsa.2017.081042
Park, B., Bae, J.K.: Using machine learning algorithms for housing price prediction: the case of Fairfax County, Virginia housing data. Expert Syst. Appl. 42(6), 2928–2934 (2015). https://doi.org/10.1016/j.eswa.2014.11.040
Pow, N., Janulewicz, E., and (Dave) Liu, L.: Applied Machine Learning Project 4 Prediction of real estate property prices in Montréal. Course project, COMP-598, Fall/2014, McGill University (2014)
Redfin: Real Estate, Homes for Sale, MLS Listings, Agents, https://www.redfin.com, last retrieved on July 15, 2022
Sagala, N.T.M. and Cendriawan, L.H.: House Price Prediction Using Linear Regression. In: 2022 IEEE 8th International Conference on Computing, Engineering and Design (ICCED), Sukabumi, Indonesia, 2022, pp. 1–5, https://doi.org/10.1109/ICCED56140.2022.10010684
Tanamal, R., Minoque, N., Wiradinata, T., Soekamto, Y., and Ratih, T.: House Price Prediction Model Using Random Forest in Surabaya City. In: Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Singapore, Dec. 2019, pp. 2215–2219. https://doi.org/10.1109/IEEM44572.2019.8978930
Truong, Q., Nguyen, M., Dang, H., Mei, B.: Housing price prediction via improved machine learning techniques. Proc. Comput. Sci. 174, 433–442 (2020). https://doi.org/10.1016/j.procs.2020.06.111
Vaddi, S.S., Yousif, A., Baraheem, S., Shen, J., and Nguyen, T.V.: House Price Prediction via Visual Cues and Estate Attributes. In: Advances in Visual Computing, ISVC 2022, Lecture Notes in Computer Science, vol. 13599, Springer, Cham, 2022, https://doi.org/10.1007/978-3-031-20716-7_8
Xu, C.: Housing Price Forecast Based on XGBoost Algorithm House Price: Advanced Regression Techniques. In: International Conference on Statistics, Data Science, and Computational Intelligence (CSDSCI 2022), vol. 12510, pp. 1251017, SPIE, 13 Jan 2023, https://doi.org/10.1117/12.2656904
Yang, R.R., Chen, S., and Chou, E.: AI Blue Book: Vehicle Price Prediction using Visual Features, arXiv:1803.11227 [cs], Mar. 2018, Accessed: Jul. 12, 2022. [Online]. Available: https://arxiv.org/abs/1803.11227v1
Yin, M.: Model for predicting london house prices. Int. J. Fin. Technol. Market Manag. 5(1), 34–42 (2023)
Zhanqi, J., Du, J.: Housing price prediction model based on XGBoost and multiple machine learning methods. Mod. Inform. Technol. 4(10), 4 (2020)
Zhou, B., Lapedriza, A., Xiao, J., Torralba, A., and Oliva, A.: Learning Deep Features for Scene Recognition using Places Database. Advances in Neural Information Processing Systems 27 (NIPS) (2014)
Zillow Real Estate, https://www.zillow.com/, last retrieved on July 15, 2022
Acknowledgements
This research was supported by the National Science Foundation (NSF) under Grant 2025234 and UD/UDRI Research Fellowship Program.
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Yousif, A., Baraheem, S., Vaddi, S.S. et al. Real estate pricing prediction via textual and visual features. Machine Vision and Applications 34, 126 (2023). https://doi.org/10.1007/s00138-023-01464-5
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DOI: https://doi.org/10.1007/s00138-023-01464-5