Machine Learning and Deep Learning-Based Housing Rental Price Prediction in China: Analysis of Endogenous and Market Factors

House price prediction has always been an important topic that attracts researchers from different fields. In this paper, an innovative house price prediction model is proposed, which comprehensively considers the intrinsic connection between various attributes of the house and the market price. This paper aims to accurately predict the reasonable price of a house under specific conditions through a variety of machine learning models, such as XGboost and artificial neural networks (ANN) and Convolutional Neural Networks(CNN), and analyze the important characteristics that determine the house price. Through the development and application of this model, this study provides more scientific and reasonable theoretical support for real estate market pricing, and also provides new research perspectives and methods for researchers in related fields.