Using linear regression model, principal components regression (PCR), and random forest to predict house prices in Hanoi
Published: July 28, 2026
Abstract
This study compared the effectiveness of three different house price prediction models, including the linear regression model, principal components regression (PCR), and random forest. Using real estate data in Hanoi, this study aimed to evaluate the predictability of each model based on independent variables, such as square footage, number of floors, number of bedrooms, and other factors. This study’s conclusion emphasized the importance of choosing the appropriate model for each specific data set to ensure accuracy and reliability in predicting house prices in Hanoi.
Keywords
modelforecastpricesreal estateHanoi
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