Housing Price Prediction Based on Multiple Linear Regression
Keyword(s):
Data Set
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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.
2020 ◽
Vol 1629
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pp. 012071
2020 ◽
Vol 8
(5)
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pp. 1801-1804
2020 ◽
Vol 10
(4)
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pp. 473-483