Guangzhou House Price Analysis based on Machine Learning Methods

With the continuous development of China's economy, Guangzhou, one of the four most powerful cities in China, has attracted many people to go and settle down there. This makes housing demand in Guangzhou continue to rise and has led to higher housing prices in recent years. In this paper, we aim to exploit the main factor, which affects the house price. Due to that, we are not able to obtain the new-house transaction. We start with second-hand housing to find the relationship. We utilize TF-IDF and K-means to analyze the data, and we conclude that the housing type is mainly related to its price, which two or three bedroom houses are with high demand and price. In contrast, houses with only one bedroom are not popular in the housing market at a low price.