Prediction of Urban House Rental Prices in Lagos - Nigeria: A Machine Learning Approach
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Published:
Aug 24, 2024
Keywords:
Machine Learning, Price Prediction, Real Estate, Regression, Random Forest
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Abstract
Often, prospective tenants need to know the rental price of an apartment, and homeowners need to know how best to price their apartments. This work aims to predict house rental prices in Lagos, Nigeria, using machine learning by examining the relationship between the rental price and features such as the number of bedrooms, bathrooms, toilets, location and house status(newly built, furnished, and/or serviced). Five machine learning models were trained and evaluated using mean absolute error (MAE), root mean squared error (RMSE) and r-square (R2); the random forest regression model outperformed the other four models with the lowest MAE, RMSE and the highest R2. This study also revealed that the number of bedrooms and the apartment's location are the most significant predictors, confirmed using the feature importance analysis. The developed model can be used to estimate the rental price of a property in Lagos, Nigeria.
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How to Cite
[1]
S. Oluyele, J. Akingbade, V. Akinode, and R. Idoghor, “Prediction of Urban House Rental Prices in Lagos - Nigeria: A Machine Learning Approach”, AJERD, vol. 7, no. 2, pp. 216-228, Aug. 2024.
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References
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[14] Oyedeji, J. O., Oshodi, O. S., & Oloke, O. C. (2018). Property Rental Value Classification Model: A Case of Osogbo, Osun State, Nigeria. Covenant Journal of Research in the Built Environment (CJRBE), 6(1), 52-64.
[15] Mathotaarachchi, K. V., Hasan, R., & Mahmood, S. (2024). Advanced Machine Learning Techniques for Predictive Modeling of Property Prices. Information, 15(6), 295. https://doi.org/10.3390/info15060295 .
[16] Kalidass, J., Dharshalini, T., Nivetha, R., & Subasri, A. (2024). House Price Prediction Using Machine Learning. International Research Journal of Engineering and Technology (IRJET), 11(4), 1351-1358.
[17] Dabreo, S., Rodrigues, S., Rodrigues, V., & Shah, P. (2021). Real Estate Price Prediction. International Journal of Engineering Research & Technology (IJERT), 10(4), 644-649.
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[19] Choy, L. H. T., & Ho, W. K. O. (2023). The Use of Machine Learning in Real Estate Research. Land, 12(4), 740. https://doi.org/10.3390/land12040740 .
[20] Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd ed.). Lawrence Erlbaum Associates, Inc.
[2] United Nations Human Settlements Programme (UN-Habitat). (2018). The State of African Cities 2018: The Geography of African Investment.
[3] Truong, Q., Nguyen, M., Dang, H., & Mei, B. (2020). Housing Price Prediction via Improved Machine Learning Techniques. Procedia Computer Science, 174(1), 433-442.
[4] Nwankwo, M. P., Onyeizu, N. M., Asogwa, E. C., & Ejike, C. O. (2023). Prediction of House Prices in Lagos-Nigeria Using Machine Learning Models.European Journal of Theoretical and Applied Sciences, 1(5), 313-326. https://doi.org/10.59324/ejtas.2023.1(5).22 .
[5] Chowhaan, M. J., Nitish, D., Akash, G., Sreevidya, N., & Shaik, S. (2023). Machine Learning Approach for House Price Prediction. Asian Journal of Research in Computer Science, 16(2), 54-61.
[6] Rawool, A. G., Rogye, D. V., Rane, S. G., & Bharadi, V. A. (2021). House Price Prediction Using Machine Learning.IRE Journals, 4(11), 29-33.
[7] Joshi, H., & Swarndeep, S. (2022). A Comparative Study on House Price Prediction using Machine Learning.International Research Journal of Engineering and Technology (IRJET), 9(11), 782-787.
[8] Aghav, V., Avhad, D., Nanaware, S., Gudekar, R., & Pawar, M. (2023). House Price Prediction Using Machine Learning. International Research Journal of Modernization in Engineering Technology and Science, 5(3), 3756-3760. https://doi.org/10.56726/IRJMETS35094 .
[9] Sisman, Y., & Sisman, A. (2016). Principal Component Analysis Approach in the Determination of House Value.Ponte Multidisciplinary Journal of Sciences and Research,72(3), 19-28. https://doi.org/10.21506/j.ponte.2016.3.23 .
[10] Mora-Garcia, R. T., Cespedes-Lopez, M.F., & Perez-Sanchez, V.R. (2022). Housing Price Prediction Using Machine Learning Algorithms in COVID-19 Times. Land, 11(2100), 22-32.
[11] Bali, K. K., & Vashistha, R. (2023, March). House Rent Prediction Using Machine Learning Algorithms – A Methodical Review. Journal of Emerging Technologies and Innovative Research, 10(3), 112-116.
[12] Abdulsalam, M. H., Thuraiya, M., Masrom, S., Johari, N., & Mohamad Saraf, M. H. (2022). Machine learning algorithms on price and rent predictions in real estate: A systematic literature review. Virtual Go Green: Conference and Publication (v-Gogreen 2021) Rethinking Built Environment: Towards a Sustainable Future, 29-30
[13] Renigier-Bilozor, M., Janowski, A., & Walacik, M. (2019). Geoscience Methods in Real Estate Market Analyses: Subjectivity Decrease. Geosciences, 9(3), 130. https://doi.org/10.3390/geosciences9030130 .
[14] Oyedeji, J. O., Oshodi, O. S., & Oloke, O. C. (2018). Property Rental Value Classification Model: A Case of Osogbo, Osun State, Nigeria. Covenant Journal of Research in the Built Environment (CJRBE), 6(1), 52-64.
[15] Mathotaarachchi, K. V., Hasan, R., & Mahmood, S. (2024). Advanced Machine Learning Techniques for Predictive Modeling of Property Prices. Information, 15(6), 295. https://doi.org/10.3390/info15060295 .
[16] Kalidass, J., Dharshalini, T., Nivetha, R., & Subasri, A. (2024). House Price Prediction Using Machine Learning. International Research Journal of Engineering and Technology (IRJET), 11(4), 1351-1358.
[17] Dabreo, S., Rodrigues, S., Rodrigues, V., & Shah, P. (2021). Real Estate Price Prediction. International Journal of Engineering Research & Technology (IJERT), 10(4), 644-649.
[18] Mouna, L. E., Silkan, H., Haynf, Y., Nann, M. F., & Tekouabou, S. C. K. (2023). A Comparative Study of Urban House Price Prediction using Machine Learning Algorithms. E3S Web of Conferences, 418, 03001. https://doi.org/10.1051/e3sconf/202341803001 .
[19] Choy, L. H. T., & Ho, W. K. O. (2023). The Use of Machine Learning in Real Estate Research. Land, 12(4), 740. https://doi.org/10.3390/land12040740 .
[20] Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd ed.). Lawrence Erlbaum Associates, Inc.