Research on the Design and Application of House Price Prediction Algorithms and Model Based on Machine Learning

With the development of the socio-economy, the real estate industry has grown rapidly worldwide. Housing prices, as an important indicator for measuring a city's economic development level, have significant impacts on people's lives, work, investments, and other aspects. Therefore, how to accurately predict housing prices has become a highly researched area of interest. In recent years, the continuous development and application of machine learning technology have provided new solutions for predicting housing prices. This article aims to study the data processing flow for housing price prediction. Through comparing and analyzing different algorithms, we will derive the optimal data processing flow and housing price prediction model, validate its prediction accuracy and stability, provide a reliable tool for the real estate industry, help make more scientific and precise decisions, and promote the continuous development of the industry.