House Price Prediction With Linear Regression
Advances in business information systems and analytics book series · 2024
This chapter illustrates a prediction for a real estate company to determine the final prices of the houses for sale based on their characteristics. A neural network tool first performs a linear regression, and then it trains a neural net. It then compares the neural net to the regression function on the testing data. It should be emphasized that the regression function has a lower root mean square error on the testing data than the neural net. Therefore, the regression function is implemented instead of the neural net, and the predictions are based on the regression.