Housing Price Prediction Based on Multiple Linear Regression

In this paper, the author first analyzes the major factors affecting housing prices with Spearman correlation coefficient, selects significant factors influencing general housing prices, and conducts a combined analysis algorithm. Then, the author establishes a multiple linear regression model for housing price prediction and applies the data set of real estate prices in Boston to test the method. Through the data analysis and test in this paper, it can be summarized that the multiple linear regression model can effectively predict and analyze the housing price to some extent, while the algorithm can still be improved through more advanced machine learning methods.

Automated summary

This paper analyzes the major factors affecting housing prices through Spearman correlation coefficient and establishes a multiple linear regression model for housing price prediction. The model is tested using real estate price data in Boston, showing that it can effectively predict and analyze housing prices to some extent, but the algorithm can still be improved through more advanced machine learning methods.