Applying kNN to Predict House Prices in Taoyuan Area

• Main Authors: Hong-Yuan Luo, 羅鴻源
• Other Authors: Jin-Lung Lin
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/742yss

碩士 === 國立東華大學 === 財務金融學系 === 107 === With the opening of Taoyuan Airport Express, the connection between Taoyuan City and Taipei City has become more and more close. It is possible that Taoyuan City will become the next Taipei or merge into the Greater Taipei Metropolitan Area. The house price of Taoyuan City has shown unprecedented potential and attracted extensive attention. Therefore, this study uses the kNN model to predict the real estate price in Taoyuan area. Firstly, the total real estate price is classified into different grades, and the actual classification and application of kNN are carried out. By randomly dividing the real estate transaction data into 9:1 and 8:2, the kNN model is established and the in-sample and out-sample predictions are made. Empirical analysis shows that the in-sample and out-of-sample predictions are highly consistent, and the prediction accuracy is as high as 0.76 and the kappa value is as high as 0.7. In addition, we also conducted a time robustness test, extracted the sample size of each year, established the kNN model through 8:2 segmentation, and made in-sample and Out-sample predictions. The empirical results confirm the robustness of the model.