Chapter 7: House Prices Prediction with Linear Regression

In Book 12: Operations Research Applications for Decision Analysis and Prediction

ISBN: 978-620-5-49772-2

Author: Vojo Bubevski (Independent Researcher)

Abstract 

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 emphasised 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.

Keywords: Prediction, Risk Analysis, Real Estate, House Prices, Neural Networks, Linear Regression.

The Results

Prediction results are presented in Table 2.

Table 2: Prediction of House Prices