This paper aims to evaluate the performance of the grey relational analysis in the forecast of housing price for the real estate market of Taiwan. An instance-based approach that used a k-nearest neighbour classifier was also applied for performance comparison. The grey relational analysis was modified to calculate the weighted synthesis of the top ten matching instances through various weighting strategies. The experimental results in this paper concluded that the grey
relational analysis outperformed the instance-based approach in terms of the mean absolute error and root mean square error. In addition, the synthesis strategy with descending weights performed better than the averaging weights during the integration process of matching instances. The result also suggested that the performance was slightly decreased if the top ten matching instances were reduced to five. The grey relational analysis integrated with the weighted synthesis model can assist both buyers and owners identify opportunities and estimate the potential risks in a worsening real estate market.

1. Al-Marwani, H. A. (2014). An approach to modeling and forecasting real estate residential property market (Doctoral dissertation).
2. Asencio-Cortes, G., Aguilar-Ruiz, J. S., & Chamorro, A. E. M. (2015). Hybrid artificial intelligent systems. Paper presented at the 10th International Conference, E. Onieva, I. Santos, E. Osaba, H. Quintian, & E. Corchado (Eds.), (pp. 5060). Cham, Germany: Springer International Publishing. https://dx.doi.org/10.1007/978-3-319-19644-2_5 https://dx.doi.org/10.1007/978-3-319-19644-2_33
3. Chen, J. H., Chang, T. T., Ho, C. R., & Diaz, J. F. (2014). Grey relational analysis and neural network forecasting of REIT returns. Quantitative Finance, 14(11), 2033-2044. https://dx.doi.org/10.1080/14697688.2013.816765
4. Deng, J. (1998). Introduction to grey system theory. The Journal of Grey System, 1(1989), 1-24.
5. Gupta, R., & Miller, S. M. (2012). The time-series properties of house prices: A case study of the Southern California market. The Journal of Real Estate Finance and Economics, 44(3), 339-361. https://dx.doi.org/10.1007/s11146-010-9234-7
6. Hu, Y., & Li, P. (2013). A grey relational analysis on factors affecting the price of commercial housing. Proceedings ICCREM, 929-936. https://dx.doi.org/10.1061/9780784413135.088
7. Janet, X., & Lam, K. C. (2012). Building a house prices forecasting model in Hong Kong. Construction Economics and Building, 2(2), 57-70. https://dx.doi.org/10.5130/ajceb.v2i2.2901
8. Jiang, C., & Yang, Z. (2015). Internet advertisements prediction. In Proceedings of 4th International Conference on Logistics, Informatics and Service Science, Z. Zhang, M. Z. Shen, J. Zhang. & R. Zhang (Eds.), (pp. 409414). Berlin, Germany: Springer Berlin Heidelberg. https://dx.doi.org/10.1007/978-3-662-43871-8_60
9. Kabakchieva, D. (2013). Predicting student performance by using data mining methods for classification. Cybernetics and Information Technologies, 13(1), 61-72. https://dx.doi.org/10.2478/cait-2013-0006
10. Ng, A. (2015). Machine learning for a london housing price prediction mobile application.
11. Park, B., & Bae, J. K. (2015). Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data. Expert Systems with Applications, 42(19), 2928-2934. https://dx.doi.org/10.1016/j.eswa.2014.11.040
12. Vijayarani, S., & Muthulakshmi, M. (2013). Comparative analysis of bayes and lazy classification algorithms. International Journal of Advanced Research in Computer and Communication Engineering, 2(8), 3118-3124.
13. Witten, I. H., & Frank, E. (2011). Data Mining: Practical machine learning tools and techniques. Morgan Kaufmann.
14. Wu, L., & Brynjolfsson, E. (2009). The future of prediction: How Google searches foreshadow housing prices and sales. SSRN Electronic Journal, 124. https://dx.doi.org/10.2139/ssrn.2022293
15. Xin, J. G., & Runeson, G. (2004). Modeling Property Prices Using Neural Network Model for Hong Kong. International Real Estate Review, 7(1), 121-138.

Tan, W., & Chou, T. (2016). Combined grey relational analysis and weighted synthesis for housing price prediction. International Journal of Business and Administrative Studies, 2(3), 102-109.